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As the need for highly trained scientists grows, a look at why people choose these careers

What leads people to a career in science?

It’s an important question because the road to a successful career in science – as with technology, engineering and mathematics, the other STEM fields – can be challenging, often requiring a Ph.D. or other postgraduate training. And once in their fields, there can be political and economic pressures with which to contend. The Bureau of Labor Statistics projects workforce shortfalls for many science fields, though the projected needs differ across the life, physical and natural sciences.

Some 55% of working Ph.D. scientists belonging to the American Association for the Advancement of Science (AAAS) who we surveyed in 2014 said this was generally a good time for their scientific specialty, while 44% said it was a bad time. And while nearly half (47%) said it was a good or very good time to begin a career in their field, 53% said it was a bad time to start out in their field.

So, what draws people into these careers? Roughly one-third (32%) of working Ph.D. scientists said a main motivator for their career path was a lifelong interest in science and desire for intellectual challenge, according to the 2014 survey . 

Many of these scientists reported an interest and curiosity in science or the natural world starting in early childhood. For some 12% their curiosity was fostered by parents and other family members who brought them in contact with scientists and science labs, nature or science and technology museums. Others (27%) remembered effective mentoring and encouragement from teachers whether in elementary school, graduate school or somewhere in between. And some 17% talked about the importance of lab and field work, often at the high school and college levels, which spurred their interest in a science career.

Men and women in this group of working Ph.D. scientists mentioned similar kinds of influences on their career choice. Women were slightly more likely than men to say that lab and internship experiences played a significant part in guiding their career path (23% of women scientists vs. 14% of men scientists). And scientists of all ages tend to cite similar kinds of influences.

Here are some of their stories:

In second grade, I read a scientific explanation of something I experienced every day. That flash of insight stimulated an intense curiosity of how things work. I knew from then on that I would be a scientist. – Molecular biologist, man, age 60

[Meseleson-Stahl]

I found science interesting. Growing up, I had a chemistry set and telescope (later building my own), and because of these, read a lot about chemistry and astronomy. My father took me rock collecting and brought chemicals home for me to analyze. Those experiences led to a degree (BS and MS) in Physics and a Ph.D. and career in Geophysics . – Geophysicist, man, age 65

[vacuum flask]

My interest in science was first piqued as a seven-year-old observing a full moon through the telescope of a friend. A couple of years later, my interest in space and the possibility of space exploration was promoted by the start of the manned launches into space in the early 1960s, and in a written essay in fourth or fifth grade I even expressed interest in science as one of three possible career paths …. – Medical Physicist, man, age 63

My entire childhood was steeped in experiences in the natural world and in scientific observation/experimentation. Both my parents are scientists. One memory that stands out in particular is of a canoe trip to the boundary waters in northern Minnesota when I was about 12, where I saw carnivorous plants in the wild for the first time – beautiful, huge, floating mats of pitcher plants …. – Ecologist, woman, age 35

While many scientists mentioned childhood experiences facilitated by their families, some 6% said science media was particularly influential in their career path. These scientists mentioned a range of media including books such as Microbe Hunters; magazines such as National Geographic and Scientific American; TV programming on PBS and commercial stations such as NOVA, Carl Sagan’s Cosmos, Mr. Wizard and Bill Nye the Science Guy.

One scientist noted:

When I was a child, my exposure through media of what science was and what scientists did influenced my career decisions. My grade school education in science was very poor, which increased the importance of the media exposure. – Biotechnologist, woman, age 54

Scientists’ reflections often touched on multiple themes; some emphasized their curiosity about the world and others emphasized the role of people in their lives who fostered their interests. As one scientist put it: “I love puzzles and to me, science is the ultimate puzzle.”

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We asked 6 scientists what inspired them to pursue a career in science. Here’s what they said

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As you read this, scientists the world over are rushing to find out more about the COVID-19 Omicron variant.

Indeed, if there’s anything the pandemic has made clear, it’s that the importance of scientific research can’t be understated in today’s world.

As we embark on a new year, hopefully with more progress on the COVID-19 front, we asked six authors of The Conversation to reflect on what first sparked their interest in science.

Read more: Hit hard by the pandemic, researchers expect its impacts to linger for years

Cathy Foley

Australia’s Chief Scientist

It was my brothers’ high-school textbooks, I kid you not! I loved poring over the Harry Messel textbooks as a 10- or 11-year-old. They were beautifully illustrated, with nature drawings and detailed experiments set out in a visual format. And I’ll never forget the photo of a dissected rat.

Then when I got to years 11 and 12 at school, the six-volume Harvard Project Physics sold me completely. It has a strong historical narrative, which is unusual in a science textbook and really worked for me.

I still have both sets of textbooks on the bookshelf in my home office. But even though I wanted to be a scientist from a young age, I didn’t know it was open to me so I didn’t dare express it. That final step only came in third-year experimental physics, when I discovered new properties of liquid crystals no one had found before. There was no going back.

Bronwyn Carlson

Professor of Indigenous Studies and Director of The Centre for Global Indigenous Futures, Macquarie University

In 2008 I made my first Facebook post. I was in the middle of a PhD, conducting interviews with Aboriginal people about their identity and involvement in the Aboriginal community. Several spoke about how they expressed their Aboriginality on Facebook, by sharing images and forming connections.

This piqued my interest; Facebook was still new, having opened to the public just two years prior. I hadn’t considered issues of identity or community in these still-novel digital settings. Back then, people tended to separate life into the offline “real” world and the online “virtual” world – which by implication was not “real”.

I became interested in whether being Aboriginal online attracted the same sort of scrutiny as Aboriginal people regularly experienced offline. It turned out those with Facebook profiles experienced high levels of surveillance around their identity. I guess regardless of being online or offline, being Indigenous can attract violent behaviour from settlers.

Postdoctoral Research Fellow at the Centre for Astrophysics and Supercomputing, Swinburne University of Technology

I have always been curious about the world and universe we live in. As a child I remember catching my poor mum off-guard, at 7.30am mind you, with the questions: “why do we exist?” and “What was there before the universe?”

It was a lot for 8-year-old me to be contemplating. But after watching all the Discovery Channel, National Geographic and History Channel documentaries I could possibly get my hands on, my mind was constantly in awe of such questions.

I genuinely can’t remember a time I haven’t been fascinated with the wonders of life. Learning physics in high school was the pinnacle of me beginning to understand why the universe is the way it is. This passion led me to where I am today – an astrophysicist and data scientist trying to make sense of the universe (and other things) via observations and data analysis.

Russell D.C. Bicknell

Postdoctoral Researcher in Palaeobiology, University of New England

When I was about five years old, my father showed me the fossil of an extinct animal called a trilobite: ancient organisms that lived within even older oceans. They evolved long before the dinosaurs, and had gone extinct just before the first of the giant vertebrates (animals that have a backbone).

In doing so, my father had introduced me to the record of organisms that were no longer alive – and furthermore, that people who studied these animals are called palaeontologists. From this point on, I was motivated to understand more about these extinct groups.

This led me down the road of studying evolution, ultimately resulting in me becoming an evolutionary palaeontologist. Now, rather true to my childhood origins, I regularly study trilobites and am interested in documenting many different aspects of arthropod evolution.

Jenny Graves

Distinguished Professor of Genetics and Vice-Chancellor’s Fellow, La Trobe University

I was a scientist for 20 years before I defined myself as “a scientist”. I was many things: harried lecturer, canny grant-seeker, cynical academic, chameleon mother and wife of shire president.

The event that stopped everything, and focused my attention on science, was a near-fatal brain bleed when I was 50 – followed by life-saving neurosurgery and an 18-month recuperation. During my rehabilitation, a kind visitor remarked comfortingly, “Now you have the space to decide what you really want to do with your life!”

I was overwhelmed by the realisation that what I really wanted to do was at the core of what I had been doing for 20 years: science! Just more, and better, with commitment and immersion.

Yvonne Wong

Associate Professor of Physics, University of New South Wales

The American physicist Sidney Coleman once said:

The career of a young theoretical physicist consists of treating the harmonic oscillator in ever-increasing levels of abstraction.

My journey into theoretical physics indeed began with a harmonic oscillator: the pendulum. Specifically, the formula relating the period of a pendulum’s swing ( T ) to its length ( l ) and gravity ( g ), which I found in a textbook at the age of about 15:

T  = 2π√( l / g )

I was always good at maths. I also liked the idea that a set of universal principles governs all natural phenomena. But to see the latter expressed in terms of the former so cleanly was an epiphany.

I spent many hours pondering the 2π and the square root. More obsessions followed, from plucked violin strings to nuclear fission.

But what sealed it in the end was Douglas Giancoli’s textbook Physics: Principles with Applications , which I came across at about age 16. The last two chapters were on “Elementary Particles” and “Astrophysics and Cosmology”. The rest is history.

Read more: There are 10 catastrophic threats facing humans right now, and coronavirus is only one of them

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How to Become a Research Scientist

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Professionals with a background in biotechnology can choose to pursue many lucrative careers . One of the most common choices is to become a research scientist. These individuals work in drug and process development, consistently conducting research and performing experiments to help move the biotechnology industry forward. 

“At the highest level, a research scientist is somebody who can design and execute experiments to prove or disprove a hypothesis,” says Jared Auclair , director of the biotechnology and bioinformatics programs at Northeastern. “Within the world of biotechnology, that can mean a number of different things, from creating new drugs to improving the process of how we make a drug.”

Professionals in this industry are often drawn to the wide array of applications of this work, as well as the consistently positive career outlook. The average salary of a biotechnology research scientist is $85,907 per year, with plenty of opportunities for increased salary potential depending on specializations, location, and years of experience. 

These factors—alongside the growing demand for advancement in biotechnology over the last few decades—have led many aspiring biotechnologists to consider a career in research science. Below we offer five steps professionals can take to kick-start a career in this field.

Download Our Free Guide to Advancing Your Biotechnology Career

Learn how to transform your career in an industry that’s transforming the world.

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5 Steps to Become a Research Scientist

1. acquire the necessary technical skills..

According to Auclair, there are four main applications of research science within the biotechnology field:

• Molecular Biology
• Process Science
• Biochemistry
• Analytical Biotechnology

Professionals hoping to pursue a career in research science must begin by deciding which of these four areas is the best fit for their interests and backgrounds. They must then acquire the specific skill sets they need to excel in that area. 

Below, Auclair breaks down some of the key skills and knowledge required within each of these specializations:

• Molecular biologists should focus on developing a complex understanding of DNA and learn how to do a Polymerase Chain Reaction alongside other DNA-related experiments. 
• Process scientists must understand cell biology and how to work with living mammalian cells, as well as how to perform analytical experiments using mass spectrometry and other analytical tools.
• Biochemists should focus on obtaining the skills necessary to make a protein drug, including the expression and purification of proteins.
• Analytical biotechnicians must become comfortable with techniques like mass spectrometry—a process that uncovers what drug products are at a molecular level.

One efficient way aspiring research scientists can obtain these specific skill sets is to pursue a master’s degree in biotechnology at a top university like Northeastern. 

“The biotech program is designed in collaboration with industry so that we’re meeting their needs,” Auclair says. “This includes training students with the skills they need to be a successful research scientist.”

The curriculum of Northeastern’s program explores the core competencies required to excel in the general biotechnology field and provides students with the unique subsets of skills they need to specialize in a specific area of research science. Students can even declare one of 10 industry-aligned concentrations, including options that directly relate with these common research science roles.

“Especially in industry, most people who are doing research science—who are actually doing the experiments and helping think about experiments with some of the senior leaders in the company—are people with a master’s degree,” Auclair says.

2. Become a critical thinker.

Alongside honing technical skills, Auclair says that critical thinking abilities are key for aspiring research scientists. 

“It’s important to become a critical thinker and a problem solver, and to challenge yourself wherever you can to step outside of your comfort zone,” Auclair says. 

Though critical thinking is a common requirement among most professional career paths, it is especially important for research scientists, who are constantly tasked with innovating and thinking creatively to solve problems.

Northeastern’s master’s in biotechnology program is designed to help students grow in this regard. “Everything we do within the program is geared [toward] making you a critical thinker and a problem solver,” Auclair says. “We try to define classes and assessments to make you think, [and] we also hire most of the faculty in our program directly from the industry, so they bring with them real-world experience that they can talk about with the students.”

These real-world case studies are a core component of Northeastern’s approach to learning, and they help prepare students to think critically about their work. By bringing this exposure into the classroom, students also graduate better prepared to tackle current industry challenges and adapt to evolving trends .

3. Hone your “power skills.”

It’s no longer enough for research scientists in biotechnology to have obtained the technical skills needed to complete their work. Today, many employers require an array of industry-specific “power skills”—previously known as “soft skills”—among candidates for research science roles.

Below we explore the top three “power skills” for biotechnology research scientists:

• Communication: As a research scientist, “you must be able to communicate scientific information to both technical and non-technical people,” Auclair says. For this reason, professionals should work to hone their verbal and written communication styles, focusing specifically on the variances in each depending on which audience they’re interacting with.
• Presentation Ability: Research scientists must be able to present their findings clearly and concisely to a variety of different audiences, ranging from fellow scientists to investors to C-suite executives. Research scientists must be comfortable in front of a group and know how to speak about their experiments and conclusions in an engaging and informative way.
• Teamwork: Although one might think a research scientist’s work is very siloed, today’s professionals must be very comfortable working with others in a lab environment. They must become comfortable sharing ideas, providing feedback to others in their cohort, and tweaking their experiments based on contributed findings.

Northeastern offers students the chance to explore each of these core “power skills” during their time within the master’s in biotechnology program. For example, the university offers countless opportunities for students to collaborate with and present to classmates, instructors, and even industry-leading organizations through Northeastern’s experiential learning opportunities, giving them the chance to apply these skills in both classroom and real-world situations early on.

Learn More: How to Become a Biotechnologist: Build Your Soft Skills

4. Obtain hands-on experience.

One of the most effective ways an aspiring research scientist can prepare for a career in this field is to obtain experiences working in a real lab. While finding these kinds of opportunities can be difficult for those just breaking into the field, programs like Northeastern’s MS in biotechnology bake hands-on learning directly into the curriculum. 

“Students do essentially four to six months [working in the] industry, and put what they learn in the classroom…into practice,” Auclair says.

These opportunities, known as co-ops , provide students with the chance to work within top organizations in the industry and explore the real-world challenges of the field from inside a functioning lab.

Did You Know: Northeastern’s program provides students with exposure to the tools and equipment used within labs in the industry. This access to cutting-edge technology reduces the learning curve and allows students to dive into their work as soon as they graduate.

Another unique way Northeastern provides hands-on experience is through Experiential Network (XN) Projects . Students who participate in these projects are typically paired with a sponsor from an active biotech company that has a real-world problem they need to solve. Then, “under the guidance of a faculty member, students spend the semester trying to come up with solutions to that problem,” Auclair says. “It’s all student-driven.”

Hands-on learning opportunities like these give students a competitive advantage when it comes to applying for jobs. “The experiential learning piece [of our program] is what has our students actually stand out above others in the field,” Auclair says, because employers like to see that their candidates are capable of applying their skills in a real-world environment. 

5. Grow your network.

Research shows that 85 percent of all jobs today are filled through networking, making it more important than ever for professionals across industries to invest time and energy into building these vital relationships.

Professionals hoping to establish a career as a research scientist are no exception. These individuals should aim to develop connections with organizations and individuals within the greater biotech industry early on in their careers, and use those relationships to help carve their path forward.

Northeastern’s master’s in biotechnology program has strategically created many great opportunities for students to network throughout their time in the program. They are encouraged to build relationships with their classmates, guest speakers, faculty, and even the industry leaders they meet through co-ops and XN projects. As a result, they establish various impactful connections with individuals at different stages in their careers, all before they graduate.

Learn More: Networking Tips for Scientists

Another way Northeastern’s program supports networking is through opportunities for student/faculty collaboration. “We encourage our students to interact with our own faculty who are research scientists as much as possible, whether that’s volunteering in their lab or finding a half an hour to talk to them about what they’re doing,” Auclair says. “We want our students to be exposed to as many research scientists as possible while they’re in the program.”

Take the Next Step

Pursuing a master’s degree in biotechnology from a top university like Northeastern is a great way for aspiring research scientists to break into the field. Students in these programs can hone related skill sets, grow their professional networks, and experience hands-on learning, all while pursuing graduate-level education. 

Learn more about how a master’s in biotechnology can set you up for success as a research scientist on our program page , then get in touch with our enrollment coaches who can help you take the first step.

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How To Become A Scientist: A New Scientist Careers Guide

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What does a scientist do?

Scientists are, by definition, individuals who study and gain expertise in one of the natural sciences: biology , chemistry , physics , astronomy and earth sciences . Each of these five main natural sciences has its own subdivisions, and the scope of work will vary for each subdivision. 

As a scientist, you will study and research a topic within one of these fields, often in great detail. Research scientists are essentially experts in specific topics within their fields.

However, even though there are many different types of scientists, the responsibilities of all research scientists are very similar.

Most scientists will need to propose their own research and gain funding for it from relevant organisations. As a scientist, you will therefore need to write up research proposals and funding applications. 

Once you start your research, you may conduct it in a lab, out in the field, or in a specialised facility, depending on the research topic. When you obtain results, you will then need to analyse them and present them to other scientists, as well as write up research papers to publish in journals or books. 

Being a scientist can be a very gratifying job, as you will often help in the development of new products. For instance, you might develop new tests as a biomedical scientist , advance technologies like artificial intelligence (AI) or work with machine learning as a computer scientist, or produce new medical guidelines as a clinical scientist .

You will also support scientists and workers in other disciplines. For example, as a data scientist you will analyse large sets of data to produce insights into datasets that may then be used in further scientific research.

How to become a scientist

Becoming a scientist requires a lot of studying and researching. Y ou wi ll need to complete an undergraduate degree in the field you woul d like to work in. F or example, if you woul d like to become a forensic scientist you should study forensic science or a related subject such as criminology. 

To obtain an undergraduate degree in a specific science, you will often need to have A levels or equivalent in particular subjects. For example, if you want to apply for a degree in biology, you will need A level biology. 

However, if you only decide what you would like to do after your secondary education, some universities offer foundation year degrees, aimed at those who don’t have a relevant A level or equivalent qualification.

After completing a bachelor’s degree, many aspiring scientists choose to do a master’s degree, and many scientists eventually also obtain a doctorate, but how common this is depends on the field.

It is important to gain some hands-on experience during your studies to become a scientist, regardless of the speciality you choose. This is because in addition to knowledge and qualifications, scientists also need to develop skills such as problem-solving, effective communication and teamwork.

Some industries, such as data science or computer science , offer postgraduate job posts for people straight out of university. These are often designed as training posts, where you will complete a training programme rotating between different teams in the company before becoming a permanent employee.

Additionally, some companies offer their employees the opportunity to undertake a fully- or partially-funded masters or even a PhD while working.  

How long does it take to become a scientist?

The exact duration of training depends on the field of study you choose. However, for most scientist jobs , it will take at least three to four years to complete the required undergraduate degree. 

It is common to then take a year to complete a master’s degree, and many scientists also undertake a PhD which can last around three to five years.

So, depending on the route you choose, you could spend between three and 10 years in education. But, for example, if you do a PhD, you will be working independently as a research scientist during that time, and will be paid for your research.  

A day in the life of a scientist

Different scientists will spend their days in different work environments and may carry out a variety of different specific tasks. Nevertheless, the broad responsibilities are often similar for many scientists across different fields of study.

For example, most research scientists will need to do tasks like proposing projects, designing and carrying out experiments in a lab or out in the field, and writing up and presenting the findings.

Other types of scientists, like engineers or computer scientists, will also need to propose projects, but they will focus less on data collection and interpretation, and more on developing new technology .  

Scientist: Career options

S cientist s work around 40 hours a week. Depending on which field they work in and what kind of role they take on , they may need to work some evenings, weekends or bank holidays, and some might even work unsocial hours. For example, research scientists will often need to spend weekends doing administrative work , forensic scientists may be called out on weekends or during the night, and computer scientists may need to work out of hours to finish projects on time.

There are many directions your science career can take. These narrow down as you choose your scientific field and subspeciality.

For example, if you know you want to study life sciences, or more specifically be a scientist in a biology-related field, you could become anything from a molecular biologist , a zoologist or a wildlife biologist to a climate change scientist.

Similarly, if you would like to study physics or maths, you might become an astrophysicist, an applied mathematician , a statistician or even an engineer.

Within most academic-oriented science careers, the natural career progression is from academic research scientist to senior research fellow, and eventually professor. This progression will require an increasing level of independence and you will need to publish original research and lead research teams to become a professor. 

As a scientist, you may also work in a more industrial setting. For example, pharmacologists often work in large pharmaceutical companies, where they help to design and research new medication, or produce already established pharmaceuticals .

Other fields, such as physics, computer science or even medical science, may have less of a research focus as you progress, and more of an applied component. For instance, as a geneticist you might progress from researching molecular genetics to a career in medical genetics and advising on genetic conditions. 

Or, as a computer scientist, you might take on managerial roles as you become more senior and lead a team of junior computer scientists to develop new software or systems.

In summary, a career in science is broad and offers many opportunities, whichever field you choose.  

How much does a scientist earn in the UK and the US?

As a research scientist in the UK, you might earn between £17,688 and £43,000 depending on your level of expertise. However, this will vary between different scientific fields. 

In the US, the salary range for a scientist is large, starting from around $50,700 to $132,100 for the best paid roles. This will, as in the UK, vary depending on your expertise, specialisation and workplace.  

References:

• National Careers Service. Research Scientist. Available from: https://nationalcareers.service.gov.uk/job-profiles/research-scientist 
• Get Educated. How to become a scientist. Available from: https://www.geteducated.com/careers/how-to-become-a-scientist/#/ 
• Career explorer. Comprehensive list of science related careers and degrees. Available from: https://www.careerexplorer.com/careers/scientist/#comprehensive-list-of-science-related-careers-and-degrees 
• Careers Wales. Scientist: How to become. Available from: https://careerswales.gov.wales/job-information/scientist/how-to-become 
• Career explorer. Scientist salary. Available from: https://www.careerexplorer.com/careers/scientist/salary/

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What does a research scientist do and how do I become one?

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As a research scientist, you’ll plan and conduct experiments to help expand the canon of scientific knowledge. With limitless opportunities for discovery across a range of high-growth sectors and industries, being a research scientist is one of the most exciting career paths in STEM. 

What does a research scientist do, exactly.

The purpose of a research scientist role is to conduct lab-based trials and experiments.

Work is often divided between pure research, which advances our understanding of basic processes, and applied research, which uses the information gathered to meet targets such as creating new products, processes, or commercial applications.

Of course, your targets will depend on the specialism of your employer. Research scientists work across a variety of different fields, including biology, chemistry, medicine, computer science, environmental science, and even political science.

Responsibilities

Typical day-to-day responsibilities of a research scientist include:

• Creating research proposals
• Planning and conducting experiments
• Collecting samples
• Monitoring experiments
• Recording and analysing data
• Collaborating with other researchers and academia to develop new techniques and products
• Supervising junior staff
• Carrying out fieldwork and monitoring environmental factors
• Researching and writing published papers
• Staying up-to-date with the latest scientific developments

Work environment

As a research scientist, you’ll spend most of your week in a laboratory. These environments can vary depending on your specialism. For example, biology labs are designed to safely house and contain living specimens, while psychology labs may simply consist of a bank of computers.

Aside from lab work, certain aspects of your role (including writing up results or research papers) will be undertaken in an office environment. You may also be required to visit the labs or offices of other researchers or companies, especially if you are collaborating on the same project.

Working hours

Research scientists typically work 35 to 40 hours a week on a 9-to-5, full-time basis. On occasion, you may be required to work overtime or visit the laboratory on weekends to complete certain tasks. That said, most organisations offer flexible working arrangements. 

What skills are needed to be a research scientist?

Though research scientists come in all personality types, you’ll need to have an academic mindset and be naturally inquisitive. Research scientist skills include:

• A methodical approach to gathering and analysing data
• Meticulous attention to detail
• Critical thinking
• Advanced research skills
• Time management
• Strong communication and interpersonal skills
• The ability to work independently
• A collaborative mindset
• Stakeholder management
• Patience and tenacity

How to become a research scientist

As a minimum requirement, you’ll need to obtain a 2:1 bachelor’s degree or higher in a relevant field of science. Most research scientists also have a postgraduate qualification, such as an MSc, an MSci or MBiol. Relevant qualifications include:

• Biochemistry
• Biomedical science
• Environmental science
• Microbiology
• Natural science
• Pharmacology

While a PhD isn’t necessarily required, some employers prefer candidates that either have or are working towards a doctorate. Demonstrable experience of working in a laboratory environment will also improve your employment chances.

Tip: If you’re currently studying or have already attained a relevant degree, try to gain research experience in a lab environment. The best place to start is by expressing your interest to your university department, who may have some voluntary positions available. Alternatively, sending your CV/resume to hospitals and STEM companies will also increase your chances of gaining that vital experience.

How much do research scientists earn?

Like many roles in science, salaries for research scientists depend on your level of experience, your specialism, the employer, and, to a lesser extent, the location. It’s also worth bearing in mind that private-sector salaries tend to be higher than those in the public sector or academia.

In the UK, research scientist salaries range from £20,000 at the entry-level to over £70,000 for university professor senior research fellow roles. The average research scientist salary is £32,330. Most research assistants earn between £26,000 and £35,000.

According to Indeed, the average salary for a research scientist in the US is $111,444.

Please note that income figures are subject to economic conditions and are only intended as a guide.

Is research scientist a good career?

With science constantly opening up exciting new avenues of research, working as a research scientist provides secure employment and gives you the chance to make a real difference within STEM.

Indeed, the outlook for the role is positive: in the US alone, the vocation is expected to grow by 8% and produce over 10,000 job opportunities across the country by 2028 (Zippia). As one of the least likely jobs to be automated in the coming years, the role also offers stability in these turbulent times. 

Offering a strong earning potential and the opportunity to conduct cutting-edge research in a range of industries and locations, research scientist represents one of the most fulfilling career paths around.

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9 Your Life and Career as a Scientist

So far, you learned ‘how to do science’. But what now? Being a scientist means that science will be a part of your life for years to come.

The way a scientist thinks and behaves informs how they carry out scientific tasks. Alongside developing your scientific knowledge and skills throughout your science degree, you will be given the opportunity to develop the personal and professional responsibility that will guide you throughout your life – professionally and personally.

This chapter explains what it means to be a scientist, which is more than just ‘doing science’. You’ll also learn about careers options, and how to use your skills once you enter the workforce.

A group of science academics, science students, employment groups and professional societies.  identified three things that a science graduate should know and be able to do regarding accountability for their own learning and scientific work by the time they graduate (Yucel, 2013). This includes:

• Being independent and self-directed learners
• Working effectively, responsibly and safely as an individual or a team
• Demonstrating knowledge of the guidelines and laws relevant to their disciplinary areas, and personally practising ethical conduct

9.1 Being independent and self-directed learners

Employers of science graduates often try to find candidates with a variety of skills such as having the ability to make decisions, being project management-minded, being resourceful and having good problem-solving abilities (Yucel, 2013).

In the workforce, science graduates often find themselves in an environment that has little direction from management, and they may need to develop or adapt new skills and understandings. Therefore, as a student scientist, learn to take responsibility for your success during your studies, so you will be prepared to continue doing so after you graduate.

To succeed in your chosen career, you will need to develop autonomy as a learner and be able to judge your own performance – Figure 9.1  shows the characteristics you will need to become an independent and self-directed learner.

Cognitive skills you need to be a good scientist

To be able to think like a scientist and conduct all of the tasks required of a scientist, you need to develop the cognitive skills lying along a continuum – from simple to complex – as shown in Bloom’s taxonomy of learning ( Figure 9.2).

Capabilities and attributes required to be a scientist

Capabilities and attributes are skills that you can demonstrate and are highly valued by employers.

Most universities have a set of skills that are referred to as ‘graduate capabilities’ and these are usually focused around similar skillsets. Sometimes graduate capabilities are referred to as ‘generic skills’ or ‘transferable skills’ – but most of all they can be thought of as ‘interdisciplinary skills’ that are important in science as well as a range of other disciplines.

Interdisciplinary skills are the foundation skills that graduates will use in their everyday work to communicate effectively, professionally, ethically, and with understanding for the diversity of the population in all occupations and disciplines (La Trobe University, 2016).

9.2 Working effectively, responsibly and safely as an individual or a team

Scientists will work both independently and in teams, and will practise working in both contexts during their undergraduate degree – see below (Whatley, 2009).

As a student scientist, it is essential that you adopt a professional approach to your scientific learning and work because this will ultimately help you to make important contributions to science and society.

Ways in which you can adopt a professional approach include:

• demonstrate the use of appropriate techniques and equipment in projects
• be organised, on time and respectful to colleagues
• demonstrate an awareness of relevant issues such as environmental, safety, community or political issues
• seek a range of information to develop and strengthen projects that you are part of
• interact with appropriate specialists to achieve agreed outcomes and develop broader knowledge
• adapt positively to change and take initiative
• complete tasks in a safe, competent and timely manner
• demonstrate professional ethics

Student scientists should conduct scientific enquiry in a manner that falls within the codes of practice for workplace health and safety. This includes considering the following when relevant:

• basic workplace health and safety
• biological safety
• chemical safety
• electrical safety
• laboratory equipment safety
• personal protective equipment
• radiation and laser safety

Team context

All scientists work in teams, and student scientists will get to practise their team work skills during their undergraduate degree. Some features of successful teams are shown in Figure 9.4.

Teams are formed when people come together to work towards a common goal

Read about how you can be an effective and efficient team member in this Good Practice Guide [PDF].

Team projects

There are several things you should consider when starting a team project:

• Get to know the rest of your team. Think of your team as puzzle pieces that can be placed together in a variety of ways (Llopis, 2012) .
• Establish team work agreements. Newly established teams should consider completing a team work agreement. It has been shown that team cohesion, trust, and awareness of members’ obligations, expectations of others and working relationships are improved when teams establish ground rules at the beginning of a project (Whatley, 2009).
• Create team goals. Decide on the big-picture goals of the team and record these (perhaps in your team agreement).
• Create task lists, and clearly define roles and responsibilities. A team should operate as a mosaic whose unique strengths and differences convert into a powerful united force (Llopis, 2012). Create a detailed task list and a time line for completion of these tasks.
• Decide on a team communication process. This includes the preferred method, frequency and nature of team communication, and ensure relevant contact details are shared. Consider making use of tools that let you communicate and collaborate with your team mates online. For example, use Zoom software for online video meetings when you can’t meet in person. Office365 and Google software allow multiple people to work together on one document, spreadsheet or presentation.
• Establish proper team dynamics. Decide on acceptable and unacceptable team dynamics, and record how unacceptable team dynamics will be dealt with should they arise (perhaps in your team agreement).

Box 9.1: Effective ways to communicate with your team

Here some effective ways to communicate with your team – compiled from past student scientists.

• Share phone numbers and email addresses
• Reply to team members in a timely fashion
• Arrive at team meetings and class on time
• Use social media to communicate
• Complete necessary and appropriate prereading
• Set small, achievable deadlines frequently
• Have a team brief at the beginning of team sessions
• Use time wisely

9.3 Guidelines, laws and ethical conduct

High-quality science graduates have an understanding of their social, cultural and environmental responsibilities as they study the natural world.

As a student scientist, you should do your best to behave ethically throughout your undergraduate study, to prepare you to become an ethical professional. Examples of ethical conduct in action include:

• accurate data recording and storage
• proper referencing and avoiding plagiarism
• intellectual integrity
• safely disposing of biological and chemical waste
• knowledge and application of the principles of animal ethics and/or human ethics.

Being an ethical scientist is more than just doing the right thing. It requires scientists to act in the right spirit, out of respect and concern for one’s fellow creatures (National Health and Medical Research Council et al., 2015).

How to be an ethical scientist – personal responsibility

Scientists and philosophers have spent their lives considering the aims of science and how scientific research should be conducted. Haque et al. summarised the most important principles displayed by an ethical scientist (Hasque et al., 2022).

How to be an ethical scientist – guidelines and laws

In many cases, the government may be involved in establishing guidelines or laws for safe and ethical behaviour.

Guidelines are sets of non-mandatory rules, principles or recommendations for procedures or practices in a particular field. Laws are rules that regulate the actions of people and may be enforced by applying penalties.

There are guidelines and laws relevant to scientists that cover experimentation and data collection, quality control procedures and appropriate safety procedures. There are also instances when you might need to obtain a government permit for a certain type of activity or research. For example, scientists and student scientists need to perform scientific work in accordance with the Workplace Health and Safety Act 2011 . This act provides a balanced and nationally consistent structure to help protect workers, including science students, against harm to their health, safety and welfare by eliminating or minimising work-related risks.

Human research

Scientists and science students involved in human research studies need to respect human research participants. They also need to comply with ethical principles of integrity, respect for persons, justice and goodness, as elaborated in the National Statement on Ethical Conduct in Human Research .

The statement is a series of guidelines developed by the National Health and Medical Research Council, the Australian Research Council and Universities Australia. These guidelines were developed to promote ethically good human research, protect participants and foster research that will benefit the community.

Unfortunately, history shows us that human research participants have not always been treated with respect. Some research studies have been done in the past that humanity should not be proud of.

Video 9.1: The worst Nobel Prize ever awarded [9 mins, 26 secs]

Note: Closed captions are available by clicking on the CC button below.

Take a look at this comprehensive research ethics timeline from 1932 to the present.

Case study 9.1: Ethics of stem cell research

Most of us have heard of stem cell research, but what exactly is it?

Stem cell research involves using embryonic stem cells or adult stem cells to learn more about human health and disease. Embryonic stem cells are derived from embryos and are highly versatile –they can give rise to any type of cell in the fully developed body. Adult stem cells are more limited, because they can only give rise to certain cells types.

Australian scientists have been at the cutting edge of stem cell research since the discovery of the human embryonic stem cell line in the late 1990s. Despite the overwhelming potential of this research to progress human health, some individuals are highly opposed to the use of embryonic stem cells because of the associated ethical issues.

There has been much debate around the ethical issues associated with stem cell research. The following videos show both US President Bush’s and Obama’s view of this research.

As you will see, world leaders don’t always agree on the ethical issues surrounding modern day scientific research:

• George W Bush on Stem Cell Research
• President Obama on Stem Cell Research

Animal research

To learn more about human health and disease, many scientists use animal models. When doing so, the welfare of the animals must be respected.

The Australian Code of Practice for the care and use of animals for scientific purposes 8th edition (2013) provides principles for the guidance of teachers, investigators, and all people involved in the care and use of animals for scientific purposes. It provides guidelines for the humane conduct of scientific and teaching activities, and for accessing animals.

The code of practice states that animals should only be used for scientific purposes when the study:

• has scientific or educational merit
• aims to benefit humans, animals or the environment
• is conducted with integrity.

In addition, the number of animals used should be minimised, the wellbeing of the animals must be supported, and harm (including pain and distress) in the animals must be avoided or minimised.

Nevertheless, the community still debates as to whether animals should be used to progress science. The following videos present both sides of this debate:

• Animal Research Laboratory
• Animal Testing Ethics
• Taboos of Science

9.4 Careers for science graduates

The great physicist Edwin Hubble, speaking at Caltech’s commencement in 1938, said a scientist has ‘a healthy skepticism, suspended judgement, and disciplined imagination’ – not only about other people’s ideas but also about his or her own. The scientist has an experimental mind, not a litigious one (Gawande, 2016). ​​

Student scientists don’t necessarily go on to a career as a laboratory-based scientist. They do, however, take their scientific literacy and skills to whatever profession they enter. Trained scientists are valuable additions to teams and companies from a range of disciplines and fields.

Australia’s former Chief Scientist Professor Ian Chubb and his office prepared a report on the importance of science, technology, engineering and mathematics (STEM) graduates in Australia’s future, which stated:

An education in STEM … fosters a range of generic and quantitative skills and ways of thinking that enable individuals to see and grasp opportunities. These capabilities – including deep knowledge of a subject, creativity, problem solving, critical thinking and communication skills – are relevant to an increasingly wide range of occupations. They will be part of the foundation of adaptive and nimble workplaces of the future (Office of the Chief Scientist, 2014, p. 7)

Throughout your undergraduate degree, you will develop a range of practical skills that will be useful in whatever professional roles you take on in the future, including:

• How to work in a laboratory
• How to reference
• How to do statistical analyses
• How to search databases
• How to talk and write about science and other topics
• How to work as part of a team
• How to present data in, for example, graphs or tables

The United Kingdom’s Science Council has identified 10 types of scientists working today (Science Council, 2016). This list highlights the fact that not all scientists end up working in laboratories – in fact, there are a wide variety of jobs that need the knowledge and skills developed during a science degree, as discussed earlier in this chapter.

Click the drop down below to review the terms learned from this chapter.

Copyright note:  Content from the following source is reproduced with permission from the copyright holder and is excluded from the Creative Commons Licence of this work. No further reproduction of this quotation is permitted without prior permission from the copyright holder.

• Whatley, J 2009, ‘Ground rules in team projects: Findings from a prototype system to support students’, Journal of Information Technology Education, 8, 161–176.

Additionally content from:

• Haque et al. (2022). A Commentary on the Importance of Ethics in Scientific Research . eScience is used under a CC-BY licence.
• Office of the Chief Scientist. (2014). Science, technology, engineering and mathematics: Australia’s future is used under a CC-BY licence.

Bloom, B.S. (1984). Taxonomy of educational objectives book 1: Cognitive domain (2nd ed.). Addison-Wesley Longman Ltd.

​Gawande, A. (2016, June 10). The mistrust of science. The New Yorker. https://www.newyorker.com/news/news-desk/the-mistrust-of-science

Hasque, M., Parvin, M., Akhter, F., & Safin, M. (2022). A commentary on the importance of ethics in scientific research. Journal of Agriculture and Aquaculture, 4 (1). https://escientificpublishers.com/importance-of-ethics-in-scientific-research-JAA-04-0037 .

La Trobe University. (2016). La Trobe essentials: Sustainability thinking. Retrieved August 12, 2016, from https://web.archive.org/web/20160801205113/www.latrobe.edu.au/essentials/sustainability-thinking

Llopis, G. (2012, October). 6 ways successful teams are built to last. Forbes. www.forbes.com/sites/ glennllopis/2012/10/01/6-ways-successfulteams-are-built-to-last/

National Health and Medical Research Council, Australian Research Council, & Australian Vice Chancellors’ Committee. (2015). National statement on ethical conduct in human research 2007, updated May 2015 (NHMRC Publication reference E72). National Health and Medical Research Council. https://www.nhmrc.gov.au/sites/default/files/documents/reports/national-statement-2015-e72.pdf

Office of the Chief Scientist. (2014). Science, technology, engineering and mathematics: Australia’s future. Australian Government. https://www.chiefscientist.gov.au/sites/default/files/STEM_AustraliasFuture_Sept2014_Web.pdf

Science Council. (2016). 10 types of scientist. Retrieved July 1, 2016, from http://sciencecouncil.org/about-us/10-types-of-scientist/

Whatley, J. (2009). Ground rules in team projects: Findings from a prototype system to support students. Journal of Information Technology Education, 8 , 161-176. https://doi.org/10.28945/165

Yucel, R. (2013). Good practice guide (Science): Threshold learning outcome 1 Understanding science. Australian Government Office for Learning and Teaching. https://www.acds.edu.au/wp-content/uploads/Science-Good-Practice-Guide-2013-TLO1.pdf

How To Do Science Copyright © 2022 by University of Southern Queensland is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Being a researcher: inspiration & curiosity to providing solutions

By Mohamed Boudjelal

The factors marking the similarities between a scientist, sportsperson and a politician are their ability to produce results, cut to the chase, lead and follow what inspired them the most. The characteristic that distinguishes the scientist from the rest, is the eagerness to discover how a certain phenomenon came about, and what is its purpose. The scientist aims to implement the gained knowledge to benefit humankind, living organisms and the universe in health, wealth, culture and sustainability. To reach this end, a scientist needs to acquire and possess certain qualities, skills and behavior regardless of his/her discipline. Based on my own experience working with successful scientists in the USA, Europe and Middle East, this short article summarizes what these qualities are.

1-        Working by inspiration not by the hours

The modern life has organized the human daily living ritual in such that most of us work very defined hours ranging from 32-40 hours a week. However, those who have left their marks in the history books, worked well beyond this schedule whether they were scientists, artists, sportspersons, politicians, writers and the like. They all shared one common quality: working by inspiration and not by the hours.  When working at or simply visiting research institutions around the world such as Harvard, MIT, MaxPlank, Karolinska, Imperial college, Welcome trust, SGC in UK and many others, one commonality that attracts your attention is this work ethic. Whether you show up during the day, the night, weekdays, weekends and holidays, there’s someone always there working to make their vision a reality. Adding to this is that there’s a noticeable level of satisfaction and enjoyment derived from such passion. The aspect that drives this motivation to work in the odd hours, is the discovery they are chasing. They get immersed in what they are doing and when a discovery is made, they don’t hesitate to call for a meeting at that exact moment whether it’s the night or a holiday to discuss it. True scientists simply enjoy working on something unique and undiscovered to make a difference in life. This does not mean, scientists do not have life beyond the lab walls. They share moments with their families and close friends. They strive to see their discoveries translated into practical changes in human development. In that regard, becoming a truly inspirational scientist, is to ignore the hours and work with inspiration. This lets you fall in love with your job, derive satisfaction and reward of what you are doing.

2-        Eagerness to be the first to know and discover

Curiosity is an intrinsic human feature; without it our life conditions would not develop and improve. It drives every person to work on the unknown, the hidden and undiscovered. The scientist uses the quality of curiosity to ask crucial questions; how a phenomenon came about and what is the benefit for mankind and how to replicate it for human use. They become satisfied when something new is discovered and no one has described it. This is in the same sense to when an athlete breaks a world record, or a politician when solving a complicated matter to stop a war. It is this unique point of being the first to the finish line that self-motivates scientists to keep going in comparison to other industries that rely on following patterns in the markets or repeating already known knowledge. It is the key characteristic the scientist must have and develop to become a true researcher who will be able discover and develop projects that impact lives positively.

3 – Thinkers out of the box

Dreaming is essential not only to human psychology, but also to humanity’s development. It can range from insignificant fragments of imagination, to concepts which alter the course of history. From a scientific perspective, such dreams often result from a drive, whether it is to understand how disease develops, or how to cure it. As scientists we have always dreamed, even speculative ideas, if at all feasible, must be explored. For example, the idea of one day having the ability to manufacture an organ in vitro to then be transplanted; or the concept of in vitro fertilization and birthing a child without a father, or even conquering space. All these aspects were no more than an impossibility for centuries, but through scientific curiosity, and abstract thinking, these dreams are now reality. Scientists must have the ability to imagine solutions beyond what is available. To enable such creativity and imagination, a scientist must keep updated on their specialty, and expose themselves to diverse thinking approaches by travelling and working worldwide. In this line, many of us have been educated in the West, and hence our way of thinking, tactic and approach to solve a scientific question is very similar. On the other hand, scientists and researchers from the East and Middle East, see through a different lens and approach problems from a different perspective. Having experience working with scientists from different cultures would challenge our methods of working and enforce new skills, providing new solutions to discover new matters. Moreover, especially in the age of information, we can easily translate non-English works to any language enabling us to further expose ourselves to other ways of thinking. Imagination and dreams are a key success of scientists, without it, we will not discover and develop new things.

4 –   Storyteller of real-life events, all are data based

Like writers and politicians, scientists tell stories based on facts and data. Unfortunately, on many occasions, the data obtained is often from experimental work, which may be surprising in such it is to the opposite of what was theorised. In such cases, most conclude that the data is negative and repeat experiments must be arranged. In other words, we avoid going deeper into those so-called negative data to understand the root cause; in reality, many times it is down to either having made a mistake in our experimental work or the data is pointing to different discovery. In this regard, no data can be deemed negative and as scientist we must ensure that what is obtained, either positive or negative, is reproducible, can be repeated, and then try to understand the message through it.

In most cases when we test a newly developed drug, it fails to show any efficacy in humans and we stop any further testing. We conclude that that drug does not work, while in vitro and even within animals it regularly produces the desired results. We halt at this stage and move on to other drugs to test.

As a scientific community, we did not come up with an approach to overcome this challenge as it is already very costly to bring a drug up to this point of testing. The negative data in this case is telling us that the disease we want to cure is different physiologically than we originally thought. One of the most important things a scientist never does, is to create or manipulate data that experiments never produce, otherwise called data fabrication to support the wanted conclusion. It is acceptable to not publish all generated data especially those that cannot yet be explained, but a true and trusted scientist never introduces data to the scientific community without guaranteeing its reproduction.  In sum a scientist must be a non-biased storyteller, based on real and reproducible data to keep their integrity and reputation.

5- Driven by the positive contribution to the whole humanity

Scientists are driven by humanity’s big picture in such that they want to contribute positively for the wellbeing of humankind and the universe. The hard work, ingenuity, curiosity and imagination must translate into the scientist’s self-satisfaction such as the discovery of chemotherapy, insulin, antibiotics, stem cells etc. Nowadays the tools available for us to try answering deeper questions and challenges are attracting the brilliant to consider science. All the impactful technology, processes and understanding began through individual discoveries in the laboratory with its application only starting after. A scientist’s role within society can often be underappreciated, but without them, humanity cannot challenge themselves to progress.

Through these 5 pillars, a scientist can achieve a professional satisfaction with a balanced family life and above all being a positive contributor to human kind and universe.

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• Home: Explore careers

Research scientist

Alternative titles for this job include.

Research scientists plan and lead experiments and investigations on a range of scientific topics.

Average salary (a year)

£27,000 Starter

£48,000 Experienced

Typical hours (a week)

39 to 41 a week

You could work

evenings / weekends / bank holidays on shifts

Jaz is a research scientist at the Natural History Museum.

Their research involves studying cells and DNA, and has even included a trip to the Arctic.

How to become

How to become research scientist.

You can get into this job through:

• a university course
• an apprenticeship
• working towards this role

You usually need a first or 2:1 (upper second class) degree in a science subject to become a research scientist. Most research scientists continue to study for a postgraduate qualification like a PhD.

You could study on an integrated postgraduate master's course. These courses include independent research and are designed to lead directly on to a PhD.

Entry requirements

You'll usually need:

• 2 or 3 A levels, or equivalent, including a science, for a degree
• a degree in a relevant subject for postgraduate study

More Information

• equivalent entry requirements
• student finance for fees and living costs
• university courses and entry requirements

Apprenticeship

You could apply to do a Research Scientist Level 7 Apprenticeship, which is equivalent to postgraduate study.

You could also join a degree apprenticeship if you want to work in a particular field of scientific research. 

Apprenticeships include:

• Biomedical Scientist Level 6
• Nuclear Scientist Level 6
• Materials Science Technologist Level 6
• Clinical Scientist Level 7

These apprenticeships can take around 3 years to complete.

To get onto an apprenticeship, you'll find it useful to have:

• 4 or 5 GCSEs at grades 9 to 4 (A* to C) and A levels, or equivalent, for a higher or degree apprenticeship
• guide to apprenticeships

It may be possible to start as a research assistant or graduate industrial scientist. You would usually need to study part time for a PhD while you work.

UK Research and Innovation and industrial companies sometimes offer studentships. This would give you the opportunity to do a PhD while getting practical research experience.

Career tips

It may improve your chances of finding work if you've got work experience in a research department, or your degree included a placement in a research environment.

As a graduate, you could look for postgraduate training opportunities offered through Knowledge Transfer Partnerships (KTP) . In a KTP you would get the opportunity to run a research project together with an organisation and a university or research body.

Further information

You can get advice about research careers from the Science Council and professional bodies for particular scientific fields, such as:

• Biochemical Society
• Royal Society of Biology
• Institute of Physics

What it takes

Skills and knowledge.

You'll need:

• science skills
• maths knowledge
• complex problem-solving skills
• thinking and reasoning skills
• to be thorough and pay attention to detail
• the ability to use your initiative
• excellent written communication skills
• the ability to work well with others
• to be able to use a computer and the main software packages confidently

What you’ll do

What you'll do, day-to-day tasks.

As a research scientist you could:

• write research proposals and apply for funding
• plan, design and do experiments
• record and analyse results
• present findings in journals and at conferences
• develop new products and ways to apply new discoveries
• teach and supervise students' research projects

Possible green job

This job could help the environment.

For a research scientist to be a green job, you could:

• carry out research which supports the environment like turning waste products into fuel
• work with reusable or recyclable equipment
• use materials from local suppliers to reduce emissions from shipping

Find out more about green careers

Working environment

You could work in a laboratory or at a university.

Your working environment may be outdoors some of the time.

You may need to wear protective clothing.

Career path and progression

As a scientist with a research council or organisation, you could move into a senior research or laboratory management position.

In an academic post, once you've gained experience and published original research, you could progress to senior research fellow or professor and lead your own research team.

You could open up further opportunities for career development by gaining Chartered Scientist status .

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What Is Research, and Why Do People Do It?

• Open Access
• First Online: 03 December 2022

Cite this chapter

You have full access to this open access chapter

• James Hiebert 6 ,
• Jinfa Cai 7 ,
• Stephen Hwang 7 ,
• Anne K Morris 6 &
• Charles Hohensee 6  

Part of the book series: Research in Mathematics Education ((RME))

18k Accesses

Abstractspiepr Abs1

Every day people do research as they gather information to learn about something of interest. In the scientific world, however, research means something different than simply gathering information. Scientific research is characterized by its careful planning and observing, by its relentless efforts to understand and explain, and by its commitment to learn from everyone else seriously engaged in research. We call this kind of research scientific inquiry and define it as “formulating, testing, and revising hypotheses.” By “hypotheses” we do not mean the hypotheses you encounter in statistics courses. We mean predictions about what you expect to find and rationales for why you made these predictions. Throughout this and the remaining chapters we make clear that the process of scientific inquiry applies to all kinds of research studies and data, both qualitative and quantitative.

You have full access to this open access chapter,  Download chapter PDF

Part I. What Is Research?

Have you ever studied something carefully because you wanted to know more about it? Maybe you wanted to know more about your grandmother’s life when she was younger so you asked her to tell you stories from her childhood, or maybe you wanted to know more about a fertilizer you were about to use in your garden so you read the ingredients on the package and looked them up online. According to the dictionary definition, you were doing research.

Recall your high school assignments asking you to “research” a topic. The assignment likely included consulting a variety of sources that discussed the topic, perhaps including some “original” sources. Often, the teacher referred to your product as a “research paper.”

Were you conducting research when you interviewed your grandmother or wrote high school papers reviewing a particular topic? Our view is that you were engaged in part of the research process, but only a small part. In this book, we reserve the word “research” for what it means in the scientific world, that is, for scientific research or, more pointedly, for scientific inquiry .

Exercise 1.1

Before you read any further, write a definition of what you think scientific inquiry is. Keep it short—Two to three sentences. You will periodically update this definition as you read this chapter and the remainder of the book.

This book is about scientific inquiry—what it is and how to do it. For starters, scientific inquiry is a process, a particular way of finding out about something that involves a number of phases. Each phase of the process constitutes one aspect of scientific inquiry. You are doing scientific inquiry as you engage in each phase, but you have not done scientific inquiry until you complete the full process. Each phase is necessary but not sufficient.

In this chapter, we set the stage by defining scientific inquiry—describing what it is and what it is not—and by discussing what it is good for and why people do it. The remaining chapters build directly on the ideas presented in this chapter.

A first thing to know is that scientific inquiry is not all or nothing. “Scientificness” is a continuum. Inquiries can be more scientific or less scientific. What makes an inquiry more scientific? You might be surprised there is no universally agreed upon answer to this question. None of the descriptors we know of are sufficient by themselves to define scientific inquiry. But all of them give you a way of thinking about some aspects of the process of scientific inquiry. Each one gives you different insights.

Exercise 1.2

As you read about each descriptor below, think about what would make an inquiry more or less scientific. If you think a descriptor is important, use it to revise your definition of scientific inquiry.

Creating an Image of Scientific Inquiry

We will present three descriptors of scientific inquiry. Each provides a different perspective and emphasizes a different aspect of scientific inquiry. We will draw on all three descriptors to compose our definition of scientific inquiry.

Descriptor 1. Experience Carefully Planned in Advance

Sir Ronald Fisher, often called the father of modern statistical design, once referred to research as “experience carefully planned in advance” (1935, p. 8). He said that humans are always learning from experience, from interacting with the world around them. Usually, this learning is haphazard rather than the result of a deliberate process carried out over an extended period of time. Research, Fisher said, was learning from experience, but experience carefully planned in advance.

This phrase can be fully appreciated by looking at each word. The fact that scientific inquiry is based on experience means that it is based on interacting with the world. These interactions could be thought of as the stuff of scientific inquiry. In addition, it is not just any experience that counts. The experience must be carefully planned . The interactions with the world must be conducted with an explicit, describable purpose, and steps must be taken to make the intended learning as likely as possible. This planning is an integral part of scientific inquiry; it is not just a preparation phase. It is one of the things that distinguishes scientific inquiry from many everyday learning experiences. Finally, these steps must be taken beforehand and the purpose of the inquiry must be articulated in advance of the experience. Clearly, scientific inquiry does not happen by accident, by just stumbling into something. Stumbling into something unexpected and interesting can happen while engaged in scientific inquiry, but learning does not depend on it and serendipity does not make the inquiry scientific.

Descriptor 2. Observing Something and Trying to Explain Why It Is the Way It Is

When we were writing this chapter and googled “scientific inquiry,” the first entry was: “Scientific inquiry refers to the diverse ways in which scientists study the natural world and propose explanations based on the evidence derived from their work.” The emphasis is on studying, or observing, and then explaining . This descriptor takes the image of scientific inquiry beyond carefully planned experience and includes explaining what was experienced.

According to the Merriam-Webster dictionary, “explain” means “(a) to make known, (b) to make plain or understandable, (c) to give the reason or cause of, and (d) to show the logical development or relations of” (Merriam-Webster, n.d. ). We will use all these definitions. Taken together, they suggest that to explain an observation means to understand it by finding reasons (or causes) for why it is as it is. In this sense of scientific inquiry, the following are synonyms: explaining why, understanding why, and reasoning about causes and effects. Our image of scientific inquiry now includes planning, observing, and explaining why.

We need to add a final note about this descriptor. We have phrased it in a way that suggests “observing something” means you are observing something in real time—observing the way things are or the way things are changing. This is often true. But, observing could mean observing data that already have been collected, maybe by someone else making the original observations (e.g., secondary analysis of NAEP data or analysis of existing video recordings of classroom instruction). We will address secondary analyses more fully in Chap. 4 . For now, what is important is that the process requires explaining why the data look like they do.

We must note that for us, the term “data” is not limited to numerical or quantitative data such as test scores. Data can also take many nonquantitative forms, including written survey responses, interview transcripts, journal entries, video recordings of students, teachers, and classrooms, text messages, and so forth.

Exercise 1.3

What are the implications of the statement that just “observing” is not enough to count as scientific inquiry? Does this mean that a detailed description of a phenomenon is not scientific inquiry?

Find sources that define research in education that differ with our position, that say description alone, without explanation, counts as scientific research. Identify the precise points where the opinions differ. What are the best arguments for each of the positions? Which do you prefer? Why?

Descriptor 3. Updating Everyone’s Thinking in Response to More and Better Information

This descriptor focuses on a third aspect of scientific inquiry: updating and advancing the field’s understanding of phenomena that are investigated. This descriptor foregrounds a powerful characteristic of scientific inquiry: the reliability (or trustworthiness) of what is learned and the ultimate inevitability of this learning to advance human understanding of phenomena. Humans might choose not to learn from scientific inquiry, but history suggests that scientific inquiry always has the potential to advance understanding and that, eventually, humans take advantage of these new understandings.

Before exploring these bold claims a bit further, note that this descriptor uses “information” in the same way the previous two descriptors used “experience” and “observations.” These are the stuff of scientific inquiry and we will use them often, sometimes interchangeably. Frequently, we will use the term “data” to stand for all these terms.

An overriding goal of scientific inquiry is for everyone to learn from what one scientist does. Much of this book is about the methods you need to use so others have faith in what you report and can learn the same things you learned. This aspect of scientific inquiry has many implications.

One implication is that scientific inquiry is not a private practice. It is a public practice available for others to see and learn from. Notice how different this is from everyday learning. When you happen to learn something from your everyday experience, often only you gain from the experience. The fact that research is a public practice means it is also a social one. It is best conducted by interacting with others along the way: soliciting feedback at each phase, taking opportunities to present work-in-progress, and benefitting from the advice of others.

A second implication is that you, as the researcher, must be committed to sharing what you are doing and what you are learning in an open and transparent way. This allows all phases of your work to be scrutinized and critiqued. This is what gives your work credibility. The reliability or trustworthiness of your findings depends on your colleagues recognizing that you have used all appropriate methods to maximize the chances that your claims are justified by the data.

A third implication of viewing scientific inquiry as a collective enterprise is the reverse of the second—you must be committed to receiving comments from others. You must treat your colleagues as fair and honest critics even though it might sometimes feel otherwise. You must appreciate their job, which is to remain skeptical while scrutinizing what you have done in considerable detail. To provide the best help to you, they must remain skeptical about your conclusions (when, for example, the data are difficult for them to interpret) until you offer a convincing logical argument based on the information you share. A rather harsh but good-to-remember statement of the role of your friendly critics was voiced by Karl Popper, a well-known twentieth century philosopher of science: “. . . if you are interested in the problem which I tried to solve by my tentative assertion, you may help me by criticizing it as severely as you can” (Popper, 1968, p. 27).

A final implication of this third descriptor is that, as someone engaged in scientific inquiry, you have no choice but to update your thinking when the data support a different conclusion. This applies to your own data as well as to those of others. When data clearly point to a specific claim, even one that is quite different than you expected, you must reconsider your position. If the outcome is replicated multiple times, you need to adjust your thinking accordingly. Scientific inquiry does not let you pick and choose which data to believe; it mandates that everyone update their thinking when the data warrant an update.

Doing Scientific Inquiry

We define scientific inquiry in an operational sense—what does it mean to do scientific inquiry? What kind of process would satisfy all three descriptors: carefully planning an experience in advance; observing and trying to explain what you see; and, contributing to updating everyone’s thinking about an important phenomenon?

We define scientific inquiry as formulating , testing , and revising hypotheses about phenomena of interest.

Of course, we are not the only ones who define it in this way. The definition for the scientific method posted by the editors of Britannica is: “a researcher develops a hypothesis, tests it through various means, and then modifies the hypothesis on the basis of the outcome of the tests and experiments” (Britannica, n.d. ).

Notice how defining scientific inquiry this way satisfies each of the descriptors. “Carefully planning an experience in advance” is exactly what happens when formulating a hypothesis about a phenomenon of interest and thinking about how to test it. “ Observing a phenomenon” occurs when testing a hypothesis, and “ explaining ” what is found is required when revising a hypothesis based on the data. Finally, “updating everyone’s thinking” comes from comparing publicly the original with the revised hypothesis.

Doing scientific inquiry, as we have defined it, underscores the value of accumulating knowledge rather than generating random bits of knowledge. Formulating, testing, and revising hypotheses is an ongoing process, with each revised hypothesis begging for another test, whether by the same researcher or by new researchers. The editors of Britannica signaled this cyclic process by adding the following phrase to their definition of the scientific method: “The modified hypothesis is then retested, further modified, and tested again.” Scientific inquiry creates a process that encourages each study to build on the studies that have gone before. Through collective engagement in this process of building study on top of study, the scientific community works together to update its thinking.

Before exploring more fully the meaning of “formulating, testing, and revising hypotheses,” we need to acknowledge that this is not the only way researchers define research. Some researchers prefer a less formal definition, one that includes more serendipity, less planning, less explanation. You might have come across more open definitions such as “research is finding out about something.” We prefer the tighter hypothesis formulation, testing, and revision definition because we believe it provides a single, coherent map for conducting research that addresses many of the thorny problems educational researchers encounter. We believe it is the most useful orientation toward research and the most helpful to learn as a beginning researcher.

A final clarification of our definition is that it applies equally to qualitative and quantitative research. This is a familiar distinction in education that has generated much discussion. You might think our definition favors quantitative methods over qualitative methods because the language of hypothesis formulation and testing is often associated with quantitative methods. In fact, we do not favor one method over another. In Chap. 4 , we will illustrate how our definition fits research using a range of quantitative and qualitative methods.

Exercise 1.4

Look for ways to extend what the field knows in an area that has already received attention by other researchers. Specifically, you can search for a program of research carried out by more experienced researchers that has some revised hypotheses that remain untested. Identify a revised hypothesis that you might like to test.

Unpacking the Terms Formulating, Testing, and Revising Hypotheses

To get a full sense of the definition of scientific inquiry we will use throughout this book, it is helpful to spend a little time with each of the key terms.

We first want to make clear that we use the term “hypothesis” as it is defined in most dictionaries and as it used in many scientific fields rather than as it is usually defined in educational statistics courses. By “hypothesis,” we do not mean a null hypothesis that is accepted or rejected by statistical analysis. Rather, we use “hypothesis” in the sense conveyed by the following definitions: “An idea or explanation for something that is based on known facts but has not yet been proved” (Cambridge University Press, n.d. ), and “An unproved theory, proposition, or supposition, tentatively accepted to explain certain facts and to provide a basis for further investigation or argument” (Agnes & Guralnik, 2008 ).

We distinguish two parts to “hypotheses.” Hypotheses consist of predictions and rationales . Predictions are statements about what you expect to find when you inquire about something. Rationales are explanations for why you made the predictions you did, why you believe your predictions are correct. So, for us “formulating hypotheses” means making explicit predictions and developing rationales for the predictions.

“Testing hypotheses” means making observations that allow you to assess in what ways your predictions were correct and in what ways they were incorrect. In education research, it is rarely useful to think of your predictions as either right or wrong. Because of the complexity of most issues you will investigate, most predictions will be right in some ways and wrong in others.

By studying the observations you make (data you collect) to test your hypotheses, you can revise your hypotheses to better align with the observations. This means revising your predictions plus revising your rationales to justify your adjusted predictions. Even though you might not run another test, formulating revised hypotheses is an essential part of conducting a research study. Comparing your original and revised hypotheses informs everyone of what you learned by conducting your study. In addition, a revised hypothesis sets the stage for you or someone else to extend your study and accumulate more knowledge of the phenomenon.

We should note that not everyone makes a clear distinction between predictions and rationales as two aspects of hypotheses. In fact, common, non-scientific uses of the word “hypothesis” may limit it to only a prediction or only an explanation (or rationale). We choose to explicitly include both prediction and rationale in our definition of hypothesis, not because we assert this should be the universal definition, but because we want to foreground the importance of both parts acting in concert. Using “hypothesis” to represent both prediction and rationale could hide the two aspects, but we make them explicit because they provide different kinds of information. It is usually easier to make predictions than develop rationales because predictions can be guesses, hunches, or gut feelings about which you have little confidence. Developing a compelling rationale requires careful thought plus reading what other researchers have found plus talking with your colleagues. Often, while you are developing your rationale you will find good reasons to change your predictions. Developing good rationales is the engine that drives scientific inquiry. Rationales are essentially descriptions of how much you know about the phenomenon you are studying. Throughout this guide, we will elaborate on how developing good rationales drives scientific inquiry. For now, we simply note that it can sharpen your predictions and help you to interpret your data as you test your hypotheses.

Hypotheses in education research take a variety of forms or types. This is because there are a variety of phenomena that can be investigated. Investigating educational phenomena is sometimes best done using qualitative methods, sometimes using quantitative methods, and most often using mixed methods (e.g., Hay, 2016 ; Weis et al. 2019a ; Weisner, 2005 ). This means that, given our definition, hypotheses are equally applicable to qualitative and quantitative investigations.

Hypotheses take different forms when they are used to investigate different kinds of phenomena. Two very different activities in education could be labeled conducting experiments and descriptions. In an experiment, a hypothesis makes a prediction about anticipated changes, say the changes that occur when a treatment or intervention is applied. You might investigate how students’ thinking changes during a particular kind of instruction.

A second type of hypothesis, relevant for descriptive research, makes a prediction about what you will find when you investigate and describe the nature of a situation. The goal is to understand a situation as it exists rather than to understand a change from one situation to another. In this case, your prediction is what you expect to observe. Your rationale is the set of reasons for making this prediction; it is your current explanation for why the situation will look like it does.

You will probably read, if you have not already, that some researchers say you do not need a prediction to conduct a descriptive study. We will discuss this point of view in Chap. 2 . For now, we simply claim that scientific inquiry, as we have defined it, applies to all kinds of research studies. Descriptive studies, like others, not only benefit from formulating, testing, and revising hypotheses, but also need hypothesis formulating, testing, and revising.

One reason we define research as formulating, testing, and revising hypotheses is that if you think of research in this way you are less likely to go wrong. It is a useful guide for the entire process, as we will describe in detail in the chapters ahead. For example, as you build the rationale for your predictions, you are constructing the theoretical framework for your study (Chap. 3 ). As you work out the methods you will use to test your hypothesis, every decision you make will be based on asking, “Will this help me formulate or test or revise my hypothesis?” (Chap. 4 ). As you interpret the results of testing your predictions, you will compare them to what you predicted and examine the differences, focusing on how you must revise your hypotheses (Chap. 5 ). By anchoring the process to formulating, testing, and revising hypotheses, you will make smart decisions that yield a coherent and well-designed study.

Exercise 1.5

Compare the concept of formulating, testing, and revising hypotheses with the descriptions of scientific inquiry contained in Scientific Research in Education (NRC, 2002 ). How are they similar or different?

Exercise 1.6

Provide an example to illustrate and emphasize the differences between everyday learning/thinking and scientific inquiry.

Learning from Doing Scientific Inquiry

We noted earlier that a measure of what you have learned by conducting a research study is found in the differences between your original hypothesis and your revised hypothesis based on the data you collected to test your hypothesis. We will elaborate this statement in later chapters, but we preview our argument here.

Even before collecting data, scientific inquiry requires cycles of making a prediction, developing a rationale, refining your predictions, reading and studying more to strengthen your rationale, refining your predictions again, and so forth. And, even if you have run through several such cycles, you still will likely find that when you test your prediction you will be partly right and partly wrong. The results will support some parts of your predictions but not others, or the results will “kind of” support your predictions. A critical part of scientific inquiry is making sense of your results by interpreting them against your predictions. Carefully describing what aspects of your data supported your predictions, what aspects did not, and what data fell outside of any predictions is not an easy task, but you cannot learn from your study without doing this analysis.

Analyzing the matches and mismatches between your predictions and your data allows you to formulate different rationales that would have accounted for more of the data. The best revised rationale is the one that accounts for the most data. Once you have revised your rationales, you can think about the predictions they best justify or explain. It is by comparing your original rationales to your new rationales that you can sort out what you learned from your study.

Suppose your study was an experiment. Maybe you were investigating the effects of a new instructional intervention on students’ learning. Your original rationale was your explanation for why the intervention would change the learning outcomes in a particular way. Your revised rationale explained why the changes that you observed occurred like they did and why your revised predictions are better. Maybe your original rationale focused on the potential of the activities if they were implemented in ideal ways and your revised rationale included the factors that are likely to affect how teachers implement them. By comparing the before and after rationales, you are describing what you learned—what you can explain now that you could not before. Another way of saying this is that you are describing how much more you understand now than before you conducted your study.

Revised predictions based on carefully planned and collected data usually exhibit some of the following features compared with the originals: more precision, more completeness, and broader scope. Revised rationales have more explanatory power and become more complete, more aligned with the new predictions, sharper, and overall more convincing.

Part II. Why Do Educators Do Research?

Doing scientific inquiry is a lot of work. Each phase of the process takes time, and you will often cycle back to improve earlier phases as you engage in later phases. Because of the significant effort required, you should make sure your study is worth it. So, from the beginning, you should think about the purpose of your study. Why do you want to do it? And, because research is a social practice, you should also think about whether the results of your study are likely to be important and significant to the education community.

If you are doing research in the way we have described—as scientific inquiry—then one purpose of your study is to understand , not just to describe or evaluate or report. As we noted earlier, when you formulate hypotheses, you are developing rationales that explain why things might be like they are. In our view, trying to understand and explain is what separates research from other kinds of activities, like evaluating or describing.

One reason understanding is so important is that it allows researchers to see how or why something works like it does. When you see how something works, you are better able to predict how it might work in other contexts, under other conditions. And, because conditions, or contextual factors, matter a lot in education, gaining insights into applying your findings to other contexts increases the contributions of your work and its importance to the broader education community.

Consequently, the purposes of research studies in education often include the more specific aim of identifying and understanding the conditions under which the phenomena being studied work like the observations suggest. A classic example of this kind of study in mathematics education was reported by William Brownell and Harold Moser in 1949 . They were trying to establish which method of subtracting whole numbers could be taught most effectively—the regrouping method or the equal additions method. However, they realized that effectiveness might depend on the conditions under which the methods were taught—“meaningfully” versus “mechanically.” So, they designed a study that crossed the two instructional approaches with the two different methods (regrouping and equal additions). Among other results, they found that these conditions did matter. The regrouping method was more effective under the meaningful condition than the mechanical condition, but the same was not true for the equal additions algorithm.

What do education researchers want to understand? In our view, the ultimate goal of education is to offer all students the best possible learning opportunities. So, we believe the ultimate purpose of scientific inquiry in education is to develop understanding that supports the improvement of learning opportunities for all students. We say “ultimate” because there are lots of issues that must be understood to improve learning opportunities for all students. Hypotheses about many aspects of education are connected, ultimately, to students’ learning. For example, formulating and testing a hypothesis that preservice teachers need to engage in particular kinds of activities in their coursework in order to teach particular topics well is, ultimately, connected to improving students’ learning opportunities. So is hypothesizing that school districts often devote relatively few resources to instructional leadership training or hypothesizing that positioning mathematics as a tool students can use to combat social injustice can help students see the relevance of mathematics to their lives.

We do not exclude the importance of research on educational issues more removed from improving students’ learning opportunities, but we do think the argument for their importance will be more difficult to make. If there is no way to imagine a connection between your hypothesis and improving learning opportunities for students, even a distant connection, we recommend you reconsider whether it is an important hypothesis within the education community.

Notice that we said the ultimate goal of education is to offer all students the best possible learning opportunities. For too long, educators have been satisfied with a goal of offering rich learning opportunities for lots of students, sometimes even for just the majority of students, but not necessarily for all students. Evaluations of success often are based on outcomes that show high averages. In other words, if many students have learned something, or even a smaller number have learned a lot, educators may have been satisfied. The problem is that there is usually a pattern in the groups of students who receive lower quality opportunities—students of color and students who live in poor areas, urban and rural. This is not acceptable. Consequently, we emphasize the premise that the purpose of education research is to offer rich learning opportunities to all students.

One way to make sure you will be able to convince others of the importance of your study is to consider investigating some aspect of teachers’ shared instructional problems. Historically, researchers in education have set their own research agendas, regardless of the problems teachers are facing in schools. It is increasingly recognized that teachers have had trouble applying to their own classrooms what researchers find. To address this problem, a researcher could partner with a teacher—better yet, a small group of teachers—and talk with them about instructional problems they all share. These discussions can create a rich pool of problems researchers can consider. If researchers pursued one of these problems (preferably alongside teachers), the connection to improving learning opportunities for all students could be direct and immediate. “Grounding a research question in instructional problems that are experienced across multiple teachers’ classrooms helps to ensure that the answer to the question will be of sufficient scope to be relevant and significant beyond the local context” (Cai et al., 2019b , p. 115).

As a beginning researcher, determining the relevance and importance of a research problem is especially challenging. We recommend talking with advisors, other experienced researchers, and peers to test the educational importance of possible research problems and topics of study. You will also learn much more about the issue of research importance when you read Chap. 5 .

Exercise 1.7

Identify a problem in education that is closely connected to improving learning opportunities and a problem that has a less close connection. For each problem, write a brief argument (like a logical sequence of if-then statements) that connects the problem to all students’ learning opportunities.

Part III. Conducting Research as a Practice of Failing Productively

Scientific inquiry involves formulating hypotheses about phenomena that are not fully understood—by you or anyone else. Even if you are able to inform your hypotheses with lots of knowledge that has already been accumulated, you are likely to find that your prediction is not entirely accurate. This is normal. Remember, scientific inquiry is a process of constantly updating your thinking. More and better information means revising your thinking, again, and again, and again. Because you never fully understand a complicated phenomenon and your hypotheses never produce completely accurate predictions, it is easy to believe you are somehow failing.

The trick is to fail upward, to fail to predict accurately in ways that inform your next hypothesis so you can make a better prediction. Some of the best-known researchers in education have been open and honest about the many times their predictions were wrong and, based on the results of their studies and those of others, they continuously updated their thinking and changed their hypotheses.

A striking example of publicly revising (actually reversing) hypotheses due to incorrect predictions is found in the work of Lee J. Cronbach, one of the most distinguished educational psychologists of the twentieth century. In 1955, Cronbach delivered his presidential address to the American Psychological Association. Titling it “Two Disciplines of Scientific Psychology,” Cronbach proposed a rapprochement between two research approaches—correlational studies that focused on individual differences and experimental studies that focused on instructional treatments controlling for individual differences. (We will examine different research approaches in Chap. 4 ). If these approaches could be brought together, reasoned Cronbach ( 1957 ), researchers could find interactions between individual characteristics and treatments (aptitude-treatment interactions or ATIs), fitting the best treatments to different individuals.

In 1975, after years of research by many researchers looking for ATIs, Cronbach acknowledged the evidence for simple, useful ATIs had not been found. Even when trying to find interactions between a few variables that could provide instructional guidance, the analysis, said Cronbach, creates “a hall of mirrors that extends to infinity, tormenting even the boldest investigators and defeating even ambitious designs” (Cronbach, 1975 , p. 119).

As he was reflecting back on his work, Cronbach ( 1986 ) recommended moving away from documenting instructional effects through statistical inference (an approach he had championed for much of his career) and toward approaches that probe the reasons for these effects, approaches that provide a “full account of events in a time, place, and context” (Cronbach, 1986 , p. 104). This is a remarkable change in hypotheses, a change based on data and made fully transparent. Cronbach understood the value of failing productively.

Closer to home, in a less dramatic example, one of us began a line of scientific inquiry into how to prepare elementary preservice teachers to teach early algebra. Teaching early algebra meant engaging elementary students in early forms of algebraic reasoning. Such reasoning should help them transition from arithmetic to algebra. To begin this line of inquiry, a set of activities for preservice teachers were developed. Even though the activities were based on well-supported hypotheses, they largely failed to engage preservice teachers as predicted because of unanticipated challenges the preservice teachers faced. To capitalize on this failure, follow-up studies were conducted, first to better understand elementary preservice teachers’ challenges with preparing to teach early algebra, and then to better support preservice teachers in navigating these challenges. In this example, the initial failure was a necessary step in the researchers’ scientific inquiry and furthered the researchers’ understanding of this issue.

We present another example of failing productively in Chap. 2 . That example emerges from recounting the history of a well-known research program in mathematics education.

Making mistakes is an inherent part of doing scientific research. Conducting a study is rarely a smooth path from beginning to end. We recommend that you keep the following things in mind as you begin a career of conducting research in education.

First, do not get discouraged when you make mistakes; do not fall into the trap of feeling like you are not capable of doing research because you make too many errors.

Second, learn from your mistakes. Do not ignore your mistakes or treat them as errors that you simply need to forget and move past. Mistakes are rich sites for learning—in research just as in other fields of study.

Third, by reflecting on your mistakes, you can learn to make better mistakes, mistakes that inform you about a productive next step. You will not be able to eliminate your mistakes, but you can set a goal of making better and better mistakes.

Exercise 1.8

How does scientific inquiry differ from everyday learning in giving you the tools to fail upward? You may find helpful perspectives on this question in other resources on science and scientific inquiry (e.g., Failure: Why Science is So Successful by Firestein, 2015).

Exercise 1.9

Use what you have learned in this chapter to write a new definition of scientific inquiry. Compare this definition with the one you wrote before reading this chapter. If you are reading this book as part of a course, compare your definition with your colleagues’ definitions. Develop a consensus definition with everyone in the course.

Part IV. Preview of Chap. 2

Now that you have a good idea of what research is, at least of what we believe research is, the next step is to think about how to actually begin doing research. This means how to begin formulating, testing, and revising hypotheses. As for all phases of scientific inquiry, there are lots of things to think about. Because it is critical to start well, we devote Chap. 2 to getting started with formulating hypotheses.

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Weisner, T. S. (Ed.). (2005). Discovering successful pathways in children’s development: Mixed methods in the study of childhood and family life . University of Chicago Press.

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Hiebert, J., Cai, J., Hwang, S., Morris, A.K., Hohensee, C. (2023). What Is Research, and Why Do People Do It?. In: Doing Research: A New Researcher’s Guide. Research in Mathematics Education. Springer, Cham. https://doi.org/10.1007/978-3-031-19078-0_1

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How to Become a Research Psychologist

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Emily is a board-certified science editor who has worked with top digital publishing brands like Voices for Biodiversity, Study.com, GoodTherapy, Vox, and Verywell.

Why Become a Research Psychologist

What do research psychologists do, where do research psychologists work, research psychology careers.

What do you do if you love psychology but have no interest in working in mental health? Fortunately, psychology is a very diverse field, and there are plenty of opportunities. One that you might consider is becoming a research psychologist.

Consider the following question from a reader:

" I love psychology, which is why I'm currently working on my bachelor's degree in psychology. I don't want to work in mental health, so my ultimate plan is to become a researcher. While I know that this means I will probably need to go to graduate school, I'm not quite sure exactly where to begin. What type of psychology degree do I need if I want to work in research?"

At a Glance

What do you do if you love psychology but don't want to become a therapist or work in mental health? You might consider becoming a research psychologist. These professionals conduct research and may work in various settings, including universities, research labs, the military, government agencies, and private businesses.

This scenario is not at all uncommon in psychology. Many students love the subject, yet are not at all interested in working in mental health settings. Experimental fields are great options for people who are fascinated by psychology and enjoy performing research.

As a psychology student , you've probably already gotten a taste of just how diverse the field can be. This can be a great thing because it allows for so many different career paths and options, but it can also be confusing for students as they struggle to select an educational path.

Just like many other areas of psychology , becoming a research psychologist is not a "one size fits all" career. There are actually many different degrees that you could potentially pursue.

Start by taking into account what type of research you want to perform and what specific topics interest you the most.

In order to decide if this field is right for you, it is important to first understand exactly what these professionals do:

• Also known as experimental psychologists , research psychologists study a broad range of human and animal behavior.
• They design and conduct experiments exploring how people act, think, behave, interact, learn, feel, and perform under different conditions.
• They also design studies and evaluate research for flaws and bias.
• This can encompass an enormous range of topics, including memory , attention, cognition, decision-making, perception, and just about any psychological topic you can think of!

If you enjoy research and still want to work in mental health, there are also mental health professionals who perform research and conduct studies in clinical settings.

Educational backgrounds and requirements for experimental psychologists can vary depending upon where you want to work.

In most cases, you will start by earning a bachelor's degree in psychology. Some students may then choose to earn a master's, but many will go on to receive a doctorate degree.

Bachelor's Degree

Many students interested in becoming research psychologists begin with a bachelor's in psychology . However, some come from a background in a related area such as social work or even from an entirely unrelated degree area altogether.

Remember, it is possible to switch to psychology for graduate school , even if your undergraduate degree is in an unrelated subject.

Master's Degree

In some cases, students might then choose to pursue a master's degree in experimental psychology. However, it is important to note that job opportunities are generally more limited with a master's degree, which is why many opt to instead go on to earn a doctorate degree in psychology .

Doctorate Degree

While you might think you are limited to earning a PhD in experimental psychology, there are actually many different options that you might opt to pursue.

For example, if you are interested in studying the human brain, you might earn a degree focused on neuropsychology. Have an active interest in social behavior? Then, you might want to consider a doctorate in social psychology .

How to Get Started

While you might not be exactly sure about what specialty you want to pursue, you can now do plenty of things to prepare for your future as a research psychologist . Start by taking as many undergraduate courses in research methods , statistics , and experimental design as possible.

Sign up for research opportunities through your school's psychology department and consider signing up as a research assistant. It's a great way to gain valuable experience while earning college credits.

As you can see, research is something that plays a significant role in virtually every field of psychology . Your goal now is to determine which particular specialty area interests you the most and exactly where you might want to work someday.

Research psychologists are employed in a wide range of sectors, including private research firms, universities, corporations, the military, and government agencies.

So what kind of jobs will you be able to get as a research psychologist? While there are many different options, a few that you might consider include:

College Professor

Many research psychologists work at colleges and universities, teaching undergraduate and graduate students and conducting research.

Research Analyst

A research analyst evaluates data that has been collected. This career involves performing statistical analyses and managing data to ensure it is collected, recorded, and analyzed properly.

Research Scientist

A research scientist conducted grant-funded research. They are often the lead investigators of a study and are responsible for hiring assistants, managing projects, designing experiments, writing journal articles, and sharing the results of their experiments.

If you enjoy research and aren't interested in working in the field of mental health, a career as a research psychologist might be a great choice for you. To enter this field, you should focus on earning an undergraduate degree in psychology before going to graduate school to get your doctorate. Taking coursework in statistics and research methodology can help, but you should also take advantage of any opportunity to participate in research.

Bishop DV. The psychology of experimental psychologists: Overcoming cognitive constraints to improve research: The 47th Sir Frederic Bartlett Lecture .  Q J Exp Psychol (Hove) . 2020;73(1):1-19. doi:10.1177/1747021819886519

Smith KV, Thew GR. Conducting research in clinical psychology practice: Barriers, facilitators, and recommendations .  Br J Clin Psychol . 2017;56(3):347-356. doi:10.1111/bjc.12142

Scholtz SE, de Klerk W, de Beer LT. The use of research methods in psychological research: A systematised review .  Front Res Metr Anal . 2020;5:1. doi:10.3389/frma.2020.00001

American Psychological Association.  Pursuing a Career in Experimental Psychology . Updated March 2014.

The Princeton Review.  Experimental Psychology .

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

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How to Become a Research Scientist

• Career Types
• Work Environment
• How to become
• Skills and Traits
• Certifications/Internship
• Career Progression

Who is a Research Scientist?

Everything that you see around you has been invented or discovered by the work of some extraordinary individuals who are known as research scientists. These individuals are responsible for carrying out scientific activities and are involved in the study of the world around them. They are also dedicated to improving the quality of life on the planet by developing new scientific methods and techniques.

If you are a science enthusiast who has a passion for the subject and is interested in learning more about the world around you, then you should consider becoming a research scientist. In addition to being involved in scientific activities, research scientists also have the opportunity to earn a living. In this article, we will be discussing how to become research scientist after 12th or how to become a research scientist in India. 

Research Scientist in a Nutshell

The passion for finding answers and the excitement of working on projects are some of the factors that make a fascinating research scientist career. However, working on a project can also expose them to various challenges and failures. A research scientist's job involves a wide variety of subjects and tasks.

Quick Facts for Research Scientist

Male, Female

Research scientist jobs are suitable for individuals who are interested in becoming a part of the technology and science industry. Both men and women can pursue this research scientist career. The right attitude and skills are some of the factors that a person should consider when it comes to choosing a research scientist career in this field.

Individuals with strong analytical and critical thinking skills can become a research scientist. There are no restrictions to this type of job, and it can be done remotely. In addition, there are various fields of science that can be done without any external efforts or physical movement. This is a perfect job for people with special needs.

Table of Contents for Research Scientist

What is the role of research scientist.

A research scientist is a person who is responsible for managing various tasks and projects, such as teams, documents, and projects. Some of them are from scratch, while others require some form of intermediary involvement. As a research scientist, you will be categorised into two categories: experimental and theoretical.

An experimental research scientist is a scientist who carries out the experiments and test results of a project. On the other hand, a theoretical research scientist is a scientist who works on the concepts and equations of a project.

The duties of a research scientist include overseeing the availability of the necessary services and equipment within the company at all times. He or she is also responsible for ensuring that the organization's policies and procedures are followed. The ideal candidate for this job would have the necessary skills and knowledge to maximize the efficiency of the company's resources.

Supervision

The duties of a research scientist include ensuring that the needs of the studies and trials are met at the centre of the care delivery process. He or she is also responsible for ensuring that the environment is safe and that the equipment used for the studies is working properly.

Team management

As a research scientist, he or she is responsible for ensuring that the various tasks and projects are carried out in a way that is consistent with the goals and objectives of the project. He or she is also expected to ensure that the team members come up with the best possible approach to the project.

Leadership Skills

Research scientists are expected to provide effective leadership and promote sound scientific practices. They are also responsible for developing support mechanisms that encourage and guide innovation in the field.

Maintenance work

As a research scientist, you will be responsible for disseminating knowledge and skills to other disciplines within the company. You will also be expected to deal with government officials and other organizations in stressful situations.

Research work

In certain situations, a research scientist's job involves carrying out a local audit and conducting research to ensure that the findings are properly disseminated. This type of work is usually carried out in order to obtain approval from the ethical council.

Types of a Research Scientist

There are various types of research scientists working in different scientific fields. These associates are responsible for analysing and disseminating scientific information.

Astronomer :  Astronomers are responsible for studying stars, galaxies, and planets. They also track the non-celestial objects in outer space. This field involves working closely with other scientists to study planetary movements.

Botanist :  As a botanist, one of the main roles of this field is to study the various aspects of the plants that are commonly found in the environment. They analyse the plant's structure, development, and uses.

Geologist :  As a Geologist, one of the most important roles in this field is to study the various elements of the Earth, including its solid, liquid, and gaseous state. He or she also studies the history and evolution of the planet.

Marine Biologist:  As a marine biologist, one of the main areas of specialisation is the study of the various marine organisms that live in the environment. This field involves analysing the interactions between plants and animals. After gaining a broad understanding of oceanography and biological oceanography, marine biologists conduct close research on different aquatic species.

What is the workplace/work environment of Research Scientist like?

As a research scientist, you will be part of a team working in different areas of the research, such as medical centres and laboratories. You will be expected to keep up with the latest developments in the field and the theoretical and experimental history of the project.

Does Research Scientist require travelling?

One of the main advantages of being a research scientist is that you will be working in a single research area, and you will typically spend about 90 per cent of your time in the OR suite. In other cases, you will be expected to work in different areas of the research, such as laboratories and experimental fields.

Employment Shifts

Full time, part time.

Research scientists are typically expected to work up to 60 hours per week, and they may also be required to be present on call during certain hours of the day. In certain facilities, where there are numerous trials, research scientists may be required to work in shifts to ensure that there are trained staff members available 24 hours a day.

Employment Nature

The nature of a research scientist's work is that it is a permanent position, which means that employers can hire them on a permanent basis. Medical centres and other third-party companies often hire research scientists.

As a research scientist, you will be expected to work in different areas of research, such as medical centres and laboratories. You will be expected to keep up with the latest developments in the field and the theoretical and experimental history of the project.

Presence in Geographical Area

Semi-urban, urban.

Tier-1 cities such as New Delhi, Bengaluru, Hyderabad, and Kolkata are known for their healthcare facilities and are known to be great places for research workers. In Tamil Nadu, the average research scientist salary is 10.6 per cent higher than the national average. In Bangalore and Karnataka, the research scientists earn more than the national average, while in Mumbai, the lowest pay is around 11.5 per cent.

Time Pressure

As a research scientist, you will be expected to work from 9 am to 5 pm, and you may be required to perform various shifts depending on the schedule.

Overtime Details

Research scientists are expected to work overtime, and this is typically done under certain circumstances. Apart from working long hours, they are also expected to perform other tasks that involve weekends and long days.

Weekly Hours of Work

Min 45 hours.

In certain facilities, where there are numerous trials, research scientists may be required to work in shifts to ensure that there are trained staff members available 24 hours a day.

How to become a Research Scientist?

Steps to become a research scientist.

If you are someone who enjoys doing research or want to know things in-depth then a career as a Research Scientist is the most suitable career for you. If you are looking for the details of how to become a research scientist in India or how to become a research scientist after 12th then you have come to the right place. We have mentioned below the steps for how to become a Research Scientist in India. 

Identify Skills

Enrol in formal training/course, pursue a specialised certification, build an attractive resume, gain experience, find a suitable job, begin a career.

To become a Research Scientist you are required to know what skills are required for a career as a Research Scientist. We have mentioned below some of the soft skills and hard skills.

Some of the soft skills for how to become a Research Scientist in India are attention to detail, communication skills, analytical skills, time management, collaboration and creativity. 

Creativity 

Curiosity 

Communication

Productivity

Formulaic Thinking 

Apart from that, you must also have some of the hard skills that are required to become a Research Scientist in India are cell culture, biochemistry, and data analysis. 

Data Analysis

Data Collection

Research Projects

Molecular Biology

Python and Java 

Cell Culture 

Experimental Design

If you are still looking for how to become a Research Scientist in India, then the most essential step for you to take is that you must opt for a formal training programme to gain knowledge in the subject and to opt for a career as a Research Scientist. You are required to complete 10+2 in Biology , Chemistry , Physics , and Mathematics from a recognised board in India. 

After you have completed your 10+2, you must opt for a bachelor’s degree by appearing for the entrance examination and then opt for a master’s degree in MSc Clinical Research or any other related degree. Below, We have mentioned the Research Scientist entrance examination, bachelor’s and master’s degrees.

Entrance Examinations

Bachelor’s Degree Programmes

Master’s Degree Programmes

If you are looking for how to become a Research Scientist in India, then you can also opt for a specialised certification. If you pursue a certification course you will gain more knowledge and skills. Below we have given some of the specialised certifications. 

Once you have completed your formal degree and certifications, you are required to create an attractive resume with all of your details such as subject knowledge and skills, your interest in the research field, and your educational background. Your resume must be in a formal and professional tone.

If you want to develop your skills and knowledge practically and gain industry experience then you must pursue an internship. Before you pursue your Ph.D. program it is better that you work for one to two years. You can upload your resume to various internship platforms, or connect directly to popular laboratories and research centers where you can work under the supervision of experienced professionals.

Once you have completed your training or internship, you can now apply for full-time job opportunities. You can apply on various job offering platforms such as Naukri, Linkedin, Monster and Indeed. Apart from that you can also approach directly to some of the laboratories or research institutes or universities. 

This is the final step in how to become a Research Scientist in India. After attending some of the related interviews you can select the best and the right offer and accept it and join the company and begin your career. 

What are the skills and qualities required to become a/an Research Scientist?

• Communication skills
• Critical thinking
• Learning Skills
• Attention to detail
• Physical strength
• Science skills

Patience:  As a research scientist, one has to remain calm and make the right decisions in order to carry out their duties. This is very important in order to maintain the continued success of the research project. The work that the associate does helps in developing new methodologies for human life.

Physical Strength: Having the proper physical strength and mental focus is very important for a research scientist to be successful in their job. Besides being physically fit, research scientist also needs to stay focused and alert during their trials, which can last for up to 8 hours.

Communication Skills:  One of the most critical skills that research scientists need to develop is communication skills. This is because, in a high-stakes environment, communicating effectively is very important.

Science Skills: People should have a deep understanding of science in order to excel in their field. This is very important for them to become a research scientist. Besides being able to excel in the field, it is also very important that they have a passion for technology.

Attention to Detail: One of the most important factors that a research scientist should consider when it comes to becoming a research scientist is the importance of paying attention to detail. This is because, in order to produce the best possible work, one must always be able to make the necessary decisions.

Critical Thinking:  As a research scientist, you must have the necessary skills to analyse and interpret data in order to make informed decisions. This discipline involves identifying the weaknesses and strengths of various solutions. Besides being able to analyse and interpret data, a research scientist also needs to have the necessary analytical skills to deal with difficult situations.

Learning Skills: In addition to being able to analyse and interpret data, a research scientist also needs to have the necessary analytical skills to deal with difficult situations. Learning skills are very important in a career as a research scientist. This discipline involves conducting various tasks such as inspecting and testing equipment.

Which certifications and internships can be helpful in becoming Research Scientist?

Individuals aspiring to become research scientist can upgrade their skills by taking various certification courses. These courses can help them perform at their best.

Internship Availability

Several organisations in the science and technology industry provide internships to students. These are designed to provide them with an opportunity to enhance their technical skills and experience, as well as learn more about becoming a research scientist. To apply, students must go through the website portals of their choice. They are also required to provide their CV and meet the requirements of the internship. Shortlisted candidates will be given various opportunities throughout the year.

Career Path Progression for Research Scientist

Junior Research Scientist:  Junior research scientists are responsible for providing technical guidance to the technicians and interns working in other fields who are under their expertise. These individuals use their knowledge in the areas they work in to improve their efficiency.

Senior Research Scientist:  A senior research scientist is a person who focuses on the principles of various engineering disciplines such as electrical, chemical, and physics. They supervise the technicians and technologists who are involved in the production or research of the project. They also prepare reports and perform other tasks to communicate engineering recommendations.

Research Scientist Jobs and Salaries

Junior research scientist.

• Average Salary 39000

Job Description

The Junior Research Scientist job description includes planning and conducting experiments, and formulating and executing investigative protocols. A Junior Research Scientist does data collection and analysis. 

Salary Description

An entry-level Junior Research Scientist salary in India ranges between Rs 2.0 Lakhs to Rs 9.8 Lakhs with an average annual salary of Rs 5.0 Lakhs per annum. Junior Research Scientist in India may vary depending on the various job factors like the skills and experience of the candidates, job location, and others.

Salary Source: AmbitionBox

Senior Research Scientist

• Average Salary 70000

The Senior Research Scientist job description includes securing the funding, publishing the findings and conducting in-house research presentations. A Senior Research Scientist promotes beneficence, minimises risks, and collects and analyses data.

The estimated Senior Research Scientist salary in India ranges from Rs 5.6 Lakhs to Rs 20.0 Lakhs with an average annual salary of Rs 10.0 Lakhs per annum. Senior Research Scientist salary may vary depending on the various job factors.

What is the job outlook for Research Scientist?

There are numerous growth opportunities in a research scientist career. You can choose to specialise in one of the areas of corporate social responsibility or develop new skills in areas such as research and development.

One of the oldest research scientist career in the industry, research scientist has plenty of scope and potential. In addition to being in the medical and biological sectors, research scientist jobs are also available in engineering technology fields. This field is heavily influenced by the discoveries made in the field of engineering, which involves the study of particulate matter.

Frequently Asked Questions for Research Scientist

Que. how to become a research scientist in biotechnology.

You must pursue a bachelor's degree by giving an entrance exam like ARS NET, JRF,  ICMR, and DBT NET and opt for a master's degree in MSc Biotechnology and must opt for an internship for atleast one to two years.  

Que. How to become a research scientist in physics?

You must pursue a bachelor's degree by giving an entrance exam like JEST, or UGC-NET and opt for a master's degree in biochemistry, biology, or pharmacology and must opt for an internship for atleast one to two years.  

Que. How to become a research scientist in biology?

You must pursue a bachelor's degree in biology by giving an entrance exam and opt for a master's degree in biochemistry, biology, or pharmacology and must opt for an internship for atleast one to two years. After that, you can opt for a PhD.

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Questions related to Research Scientist

Which is the best msc in microbiology or msc in bio physicsin terms of jobs as a research scientist after completing my bsc degree in microbiology ....

Hello Aspirant,

There are numerous opportunities ahead for graduates of M.Sc Microbiology. The scope has risen for M.Sc. microbiology graduates with the emergence of COVID. The demand for researchers has constantly increased to determine whether its existence in the human ecosystem is natural or man-made.

An M.Sc. in microbiology provides numerous opportunities in various fields such as education, healthcare, pharmaceutical, and agriculture.

Graduates can find career opportunities in both the private as well as public sectors. The agriculture sector also demands skilled professionals for microbiological research on subjects like rhizosphere, nitrogen fixation, biogas production, soil enzymes, and anaerobic decomposition.

Further, you can know more about the top colleges, salary packages, etc at https://www.careers360.com/courses/msc-in-microbiology#:~:text=Benefits%20of%20Studying%20M.Sc%20Microbiology%20A%20M.Sc.%20in,both%20the%20private%20as%20well%20as%20public%20s

MSc Biophysics: Biophysics is an advanced field of science that uses the techniques of physical science to study biological systems.

Benefits of studying biophysics:

1. Biophysicists can also work in universities, industry, medical centers, research institutes, and government.

2. Candidates can find jobs as biophysics researchers or scientists with research institutes or government organizations in various academic grades for research-oriented programs.

3. The course is beneficial for those who are curious about biological processes and enjoy puzzle solving, designing experiments, or working with numbers and computers, there are many exciting opportunities for you in biophysics.

4. They can even find a job as a professor or member of faculty in a university, medical or dental college offering a program in biophysics.

Further, You can know about this course at https://www.careers360.com/courses/bio-physics-course

In the end, what matters the most is in which area your interest lies and the amount of hard work you put into it.

Best Wishes!

I wanted to ask that do research scientist ( I mean kvpy scholar) earn good amount of money in India ?

Dear aspirant,

Department of Science and Technology, Government of India has started Kishore Vaigyanik Protsahan Yojana or Young Scientist Incentive Plan for encouraging young scientists in pursuing research career courses in basis sciences upto Pre-Ph.D level.

The KVPY students receive a amout of Rs. 5000 monthly fellowship from first year of degree to final year of degree in courses like Integrated M.S or M.Sc, B.Sc or B. Statistics or B. Mathematics or B.S Maths/ Integrated M.S./M.Sc. They receive amount of Rs. 20,000 per year as annual contingency grant. After 3 years the amount is increased to Rs. 7000 and annual grant of Rs. 28,000 is given.

Candidates can also get DST Inspire Scholarship with worth of Rs. 80,000 per annum. The scholarship is given on the basis of Skill test conducted every year.

I hope this information was useful to you.

Best of Luck!!

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How To Become an AI Research Scientist

As we know, Artificial Intelligence (AI) is really important. It helps businesses do things better and find new chances. That’s why there’s a big need for smart AI scientists. They make good money because they know a lot and help companies do cool things with AI. AI can do a lot of stuff, and it’s getting more popular. So, being an AI scientist is a big deal right now.

In this article, we will explore the Steps to becoming an AI Research Scientist including Educational Background, Experience, Skills Required, Practical Experience and other advanced career Steps.

Table of Content

Who are AI Research Scientists?

How to become an ai research scientist – roadmap 2024, 1. educational background, 2. gain practical experience, 3. develop technical skills, 4. specialize in key ai domains, 5. share your insights and research, 6. networking and collaboration, 7. continuous learning, 8. advanced career steps.

AI research scientists command substantial salaries, reflecting their expertise and the value they bring to organizations. However, beyond financial incentives, the opportunity to pioneer groundbreaking discoveries and contribute to the advancement of AI technology is a compelling draw for many aspiring scientists.

Embarking on the journey to become an AI research scientist requires a strategic approach and a commitment to continuous learning. Here’s a roadmap to guide aspiring scientists towards their goals:

• Major: Computer Science, Mathematics, Engineering, or related fields.
• Key Courses: Machine Learning , Data Structures, Algorithms, Probability and Statistics, Linear Algebra, Calculus, Programming Languages.
• Master’s Degree: A specialized Master’s program in AI, Machine Learning, or Data Science offers in-depth exploration of advanced concepts. Students delve into specialized topics such as Deep Learning , Reinforcement Learning , and Bayesian Methods. Practical projects and internships provide hands-on experience and networking opportunities.
• PhD (optional but recommended): Conduct research in a specialized area of AI. This is crucial for a research career, particularly in academia or advanced industry roles.
• Internship and Research Assistantships: Interning at tech companies or assisting in academic research projects offers invaluable hands-on experience. Interns work alongside seasoned professionals, gaining exposure to real-world challenges and industry best practices. Research assistantships provide opportunities to contribute to ongoing research projects, collaborate with faculty members, and publish papers.
• Personal Projects and Kaggle Competitions: Engaging in personal AI projects allows for experimentation and skill development. Building AI models and applications from scratch fosters creativity and problem-solving abilities. Participating in competitions like Kaggle provides exposure to diverse datasets and challenges, encouraging collaboration and innovation within the AI community.
• Programming Languages: Python is the de facto language for AI development due to its simplicity, versatility, and rich ecosystem of libraries. Proficiency in Python enables efficient implementation of AI algorithms and models. Additionally, knowledge of languages like R , C++ , or Java expands one’s toolkit for specific tasks or projects.
• Tools and Frameworks: Familiarity with popular AI libraries such as TensorFlow , PyTorch, and Scikit-learn is essential for model development and experimentation. Proficiency in data manipulation libraries like Pandas and NumPy streamlines data preprocessing and analysis. Visualization tools like Matplotlib and Seaborn facilitate data exploration and presentation.
• Machine Learning: Supervised and unsupervised learning, reinforcement learning.
• Deep Learning: Neural networks, CNNs, RNNs, GANs.
• Natural Language Processing (NLP): Text processing, transformers, language models.
• Computer Vision: Image processing, object detection, segmentation.
• Publish Research: Disseminating research findings through publications is essential for contributing to the collective knowledge of the AI community. Submitting papers to prestigious conferences and journals provides visibility and recognition within academic and industry circles. Additionally, sharing preprints on platforms like ArXiv allows for early feedback and collaboration opportunities.
• Online Presence: Establishing an online presence through platforms like GitHub showcases your projects and contributions to the AI community. Maintaining a blog or personal website allows for sharing insights, tutorials, and research updates. Engaging with peers through forums and social media platforms fosters collaboration and knowledge exchange.
• Professional Associations: Joining professional organizations like the Institute of Electrical and Electronics Engineers (IEEE) and the Association for Computing Machinery (ACM) connects you with like-minded professionals and provides access to conferences, workshops, and publications. Membership offers opportunities for networking, mentorship, and staying abreast of the latest developments in AI research and technology.
• Conferences and Workshops: Attending and presenting at AI conferences and workshops is invaluable for networking and professional development. Interacting with researchers, practitioners, and industry experts allows for exchanging ideas, forming collaborations, and gaining insights into emerging trends and technologies.
• Online Courses and Certifications: Lifelong learning is essential in the rapidly evolving field of AI. Online platforms like Coursera, edX, and Udacity offer a plethora of courses and certifications covering advanced machine learning techniques, specialized AI topics, and research methodologies. Engaging in continuous learning ensures that you stay updated on the latest advancements and maintain relevance in the competitive AI landscape.
• Stay Updated: Keeping abreast of the latest research papers, books, and industry developments is crucial for staying ahead in AI. Regularly reading seminal papers, textbooks, and blogs by thought leaders provides insights into cutting-edge research, methodologies, and best practices. Actively participating in online forums and discussion groups allows for exchanging ideas, seeking advice, and contributing to the AI community.
• Postdoctoral Fellowships: Postdoctoral research positions offer opportunities for deepening expertise, exploring new research directions, and building a strong research portfolio. Postdocs collaborate with leading researchers, publish high-impact papers, and prepare for academic or industry leadership roles.
• Industry Roles: AI research scientists play pivotal roles in research labs of leading tech companies, driving innovation and developing cutting-edge AI solutions. They contribute to product development, collaborate with interdisciplinary teams, and push the boundaries of AI technology. Alternatively, AI consultants leverage their expertise to provide strategic guidance and solutions to organizations across various industries.
• Academic Pursuits: Pursuing faculty positions in academia allows AI research scientists to lead research teams, mentor students, and shape the future of AI education and research. As professors or lecturers, they conduct groundbreaking research, secure funding, and disseminate knowledge through teaching and publication. Academic roles offer autonomy, intellectual freedom, and opportunities for long-term impact on the field of AI.

Becoming an AI Research Scientist is a challenging yet rewarding journey. It requires a strong educational foundation, practical experience, specialized skills, and continuous learning. By following this roadmap, you can systematically build your career and contribute to the exciting field of artificial intelligence

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The 5 Best Udemy Courses That Are Worth Taking in 2024

Udemy is an online platform for learning at your own pace. Boost your career with our picks for the best Udemy courses for learning tech skills online in 2024.

What Is Data Quality? Definition and Best Practices

Data quality refers to the degree to which data is accurate, complete, reliable and relevant for its intended use.

TechRepublic Premium Editorial Calendar: Policies, Checklists, Hiring Kits and Glossaries for Download

TechRepublic Premium content helps you solve your toughest IT issues and jump-start your career or next project.

What is the EU’s AI Office? New Body Formed to Oversee the Rollout of General Purpose Models and AI Act

The AI Office will be responsible for enforcing the rules of the AI Act, ensuring its implementation across Member States, funding AI and robotics innovation and more.

What is Data Science? Benefits, Techniques and Use Cases

Data science involves extracting valuable insights from complex datasets. While this process can be technically challenging and time-consuming, it can lead to better business decision-making.

Gartner’s 7 Predictions for the Future of Australian & Global Cloud Computing

An explosion in AI computing, a big shift in workloads to the cloud, and difficulties in gaining value from hybrid cloud strategies are among the trends Australian cloud professionals will see to 2028.

OpenAI Adds PwC as Its First Resale Partner for the ChatGPT Enterprise Tier

PwC employees have 100,000 ChatGPT Enterprise seats. Plus, OpenAI forms a new safety and security committee in their quest for more powerful AI, and seals media deals.

What Is Contact Management? Importance, Benefits and Tools

Contact management ensures accurate, organized and accessible information for effective communication and relationship building.

How to Use Tableau: A Step-by-Step Tutorial for Beginners

Learn how to use Tableau with this guide. From creating visualizations to analyzing data, this guide will help you master the essentials of Tableau.

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