computer research scientist meaning

What does a computer and information research scientist do?

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What is a Computer and Information Research Scientist?

Computer and information research scientists conduct advanced research and studies in the field of computer science, information technology, and related areas. They explore new possibilities in computer hardware and software, algorithms, data analysis, artificial intelligence, and other emerging technologies. They may specialize in areas such as machine learning, cybersecurity, data mining, computer graphics, or networking.

Computer and information research scientists publish research papers, present at conferences, and contribute to the scientific community's knowledge and understanding of computer science. Their research findings and discoveries contribute to the development of new products, technologies, and applications that can impact various industries, such as healthcare, finance, communications, and entertainment.

What does a Computer and Information Research Scientist do?

A computer and information research scientist working on her computer.

Computer and information research scientists play an important role in driving technological innovation and shaping the future of computing by exploring new frontiers, solving complex problems, and advancing the field through their research efforts.

Duties and Responsibilities Here are some common responsibilities associated with the role of a computer and information research scientist:

Research and Experimentation: Conducting advanced research and experimentation to explore new ideas, technologies, and approaches within the field of computer science. This involves formulating research questions, designing experiments, collecting and analyzing data, and drawing conclusions based on the results.
Technology Development: Developing new technologies, algorithms, models, or software solutions to address complex problems and push the boundaries of computer science. This includes designing innovative systems, architectures, or methodologies that can improve computer performance, efficiency, security, or user experience.
Data Analysis and Modeling: Analyzing large datasets, applying statistical techniques, and developing models to gain insights, predict trends, or solve specific problems. This involves utilizing techniques such as machine learning, data mining, or data visualization to extract meaningful information and make informed decisions.
Software and Algorithm Design: Designing and developing software applications, algorithms, or programming languages that enable new functionalities or solve specific computational challenges. This includes writing code, debugging, testing, and optimizing software to ensure its efficiency, reliability, and scalability.
Collaboration and Communication: Collaborating with other researchers, engineers, and professionals in interdisciplinary teams to exchange ideas, share knowledge, and work towards common goals. Effective communication skills are essential for presenting research findings, writing scientific papers, and delivering presentations at conferences or seminars.
Technology Evaluation and Assessment: Evaluating existing technologies, systems, or methodologies to identify their strengths, weaknesses, and potential improvements. This involves staying abreast of the latest advancements in the field, assessing their relevance, and providing recommendations for their implementation or refinement.
Project Management: Planning, organizing, and managing research projects, including setting objectives, allocating resources, and ensuring timely completion of tasks. This may involve supervising and mentoring junior researchers, coordinating collaborations with external partners, and overseeing the overall progress of the project.
Publication and Knowledge Sharing: Publishing research findings in academic journals, presenting at conferences, and contributing to the scientific community's knowledge base. This includes writing research papers, participating in peer reviews, and staying actively engaged in professional networks and forums.
Ethical Considerations: Adhering to ethical guidelines and principles in research, particularly when working with sensitive data, artificial intelligence, or human subjects. Ensuring that research practices comply with legal and ethical standards is crucial for maintaining integrity and accountability in the field.

Types of Computer and Information Research Scientists Here are some common types of computer and information research scientists based on their specializations:

Artificial Intelligence (AI) Research Scientist: Specializes in the development and advancement of AI technologies, including machine learning, natural language processing, computer vision, and robotics. They focus on creating intelligent systems that can learn, reason, and perform tasks autonomously.
Data Scientist : Focuses on analyzing and interpreting large datasets to extract insights, identify patterns, and make data-driven decisions. They utilize statistical and computational techniques, as well as machine learning algorithms, to uncover meaningful information from complex data.
Network Research Scientist: Specializes in the design, development, and optimization of computer networks. They focus on areas such as network protocols, network security, network performance analysis, and the development of innovative networking technologies.
Security Research Scientist: Concentrates on researching and developing techniques to protect computer systems, networks, and data from cyber threats. They work on areas such as cryptography, secure software development, intrusion detection, vulnerability analysis, and security protocols.
Human-Computer Interaction (HCI) Research Scientist: Studies the interaction between humans and computer systems, with a focus on improving user experience, usability, and accessibility. They investigate user behavior, design intuitive interfaces, and develop interactive technologies that better meet users' needs.
Computer Graphics and Visualization Research Scientist: Specializes in the development and enhancement of computer graphics algorithms, 3D modeling, virtual reality, augmented reality, and data visualization techniques. They work on creating visually compelling and interactive computer-generated imagery.
Software Engineering Research Scientist: Concentrates on advancing software development methodologies, tools, and practices. They research software architecture, software testing, software quality assurance, and other areas to improve the efficiency, reliability, and maintainability of software systems.
Natural Language Processing (NLP) Research Scientist: Focuses on understanding and processing human language by computers. They work on tasks such as machine translation, sentiment analysis, information retrieval, and automated speech recognition to enable computers to understand and generate human language.
Quantum Computing Research Scientist: Specializes in the field of quantum computing, which involves developing algorithms, designing quantum circuits, and exploring the potential applications of quantum technologies. They work on harnessing the power of quantum mechanics to solve complex computational problems.

Are you suited to be a computer and information research scientist?

Computer and information research scientists have distinct personalities . They tend to be investigative individuals, which means they’re intellectual, introspective, and inquisitive. They are curious, methodical, rational, analytical, and logical. Some of them are also artistic, meaning they’re creative, intuitive, sensitive, articulate, and expressive.

Does this sound like you? Take our free career test to find out if computer and information research scientist is one of your top career matches.

What is the workplace of a Computer and Information Research Scientist like?

The workplace of a computer and information research scientist can vary depending on their specific role, employer, and area of specialization. Generally, they work in environments that foster research, innovation, and collaboration. Here is a description of the typical workplaces for these professionals:

Research Laboratories: Many computer and information research scientists work in research laboratories, either in academic institutions or private companies. These labs provide a dedicated space for conducting experiments, developing prototypes, and analyzing data. Research laboratories are equipped with advanced computer systems, high-performance servers, specialized software, and cutting-edge research tools to support their work.

Academic Institutions: Research scientists in computer and information science often work in universities or research institutes. They may be affiliated with a particular department or research center within the institution. Academic environments provide access to extensive research resources, such as libraries, research grants, and collaborations with other faculty members and students.

Industrial Research and Development (R&D) Centers: Many large technology companies have dedicated R&D centers where computer and information research scientists work on developing new technologies, software, or hardware products. These centers provide a stimulating and innovative environment with access to state-of-the-art facilities, collaborative teams, and resources for bringing research ideas to practical applications.

Government Research Agencies: Some computer and information research scientists work in government research agencies, such as national laboratories or defense research organizations. These agencies focus on research and development in areas of national interest, including cybersecurity, data analysis, information assurance, and emerging technologies. Government research agencies often collaborate with academia and industry on projects of strategic importance.

Collaboration and Fieldwork: Depending on their research focus, computer and information research scientists may engage in collaborative projects with other researchers, industry partners, or government agencies. This can involve fieldwork, where they collect data or conduct experiments in real-world settings. For example, researchers studying human-computer interaction may conduct user studies in various environments to gather data and evaluate the usability of systems.

Conferences and Workshops: Research scientists often attend conferences, workshops, and seminars relevant to their areas of expertise. These events provide opportunities to present research findings, exchange ideas, and network with other professionals in the field. Presenting research at conferences enables scientists to receive feedback, gain exposure, and stay updated with the latest developments in their areas of research.

Collaboration Tools and Remote Work: With advancements in communication technology, computer and information research scientists may also work remotely or utilize collaboration tools to work with colleagues from different locations. Remote work and virtual collaboration platforms allow for global collaboration, enabling scientists to collaborate with experts from around the world and exchange ideas without physical constraints.

Computer and Information Research Scientists are also known as: Computer Research Scientist

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Computer and Information Research Scientists: Jobs, Career, Salary and Education Information

Computer and Information Research Scientists

Career, salary and education information.

What They Do : Computer and information research scientists invent and design new approaches to computing technology and find innovative uses for existing technology.

Work Environment : Most computer and information research scientists work full time. Some work more than 40 hours per week.

How to Become One : Most jobs for computer and information research scientists require a master’s degree in computer science or a related field. In the federal government, a bachelor’s degree may be sufficient for some jobs.

Salary : The median annual wage for computer and information research scientists is $131,490.

Job Outlook : Employment of computer and information research scientists is projected to grow 21 percent over the next ten years, much faster than the average for all occupations.

Related Careers : Compare the job duties, education, job growth, and pay of computer and information research scientists with similar occupations.

Following is everything you need to know about a career as a computer or information research scientist with lots of details. As a first step, take a look at some of the following jobs, which are real jobs with real employers. You will be able to see the very real job career requirements for employers who are actively hiring. The link will open in a new tab so that you can come back to this page to continue reading about the career:

Top 3 Computer Scientist Jobs

JOB SUMMARY -- ESSENTIAL FUNCTIONS/DUTIES Under general supervision, a Computer Scientist II provides software and systems engineering services, generally as a member of a work unit or group

Exploring Computer Science * Digital Marketing If you have any questions regarding the position, please contact Michael Douglas, Principal, at (385) 646-5264 or email [email protected]

Computer Science Instructor Salesian High School 148 Main Street New Rochelle, NY 10802 Salesian High School is seeking qualified candidates for the position of Computer Science Instructor for the ...

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Top 3 Information Research Scientist Jobs

Research Scientist Job statement: The Research Scientist 's role is to develop novel molecular ... Identify and synthesize key information from internal and external knowledge bases to take charge ...

The blocks that form our foundational teams -- People, Finance, Counsel, Hardware, Information ... As a Research Scientist at Dessa, you will create novel deep learning systems with the capability ...

Create mathematically principled solutions to some of the world's most challenging information ... A Research Scientist at Numerica should possess an M.S. or Ph.D. in Applied or Computational ...

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What Computer and Information Research Scientists Do [ About this section ] [ To Top ]

Computer and information research scientists invent and design new approaches to computing technology and find innovative uses for existing technology. They study and solve complex problems in computing for business, science, medicine, and other fields.

Duties of Computer and Information Research Scientists

Computer and information research scientists typically do the following:

Explore fundamental issues in computing and develop theories and models to address those issues
Help scientists and engineers solve complex computing problems
Invent new computing languages, tools, and methods to improve the way in which people work with computers
Develop and improve the software systems that form the basis of the modern computing experience
Design experiments to test the operation of these software systems
Analyze the results of their experiments
Publish their findings in academic journals and present their findings at conferences

Computer and information research scientists create and improve computer software and hardware.

Creating and improving software involves working with algorithms, which are sets of instructions that tell a computer what to do. Some computing tasks are very difficult and require complex algorithms. Computer and information research scientists try to simplify these algorithms to make computer systems as efficient as possible. The algorithms allow advancements in many types of technology, such as machine learning systems and cloud computing.

Computer and information research scientists design new computer architecture that improves the performance and efficiency of computer hardware. Their work often leads to technological advancements and efficiencies, such as better networking technology, faster computing speeds, and improved information security. In general, computer and information research scientists work at a more theoretical level than do other computer professionals.

Some computer scientists work with electrical engineers , computer hardware engineers , and other specialists on multidisciplinary projects. The following are examples of types of specialties for computer and information research scientists:

Data science. Computer and information research scientists write algorithms that are used to detect and analyze patterns in very large datasets. They improve ways to sort, manage, and display data. Computer scientists build algorithms into software packages that make the data easier for analysts to use. For example, they may create an algorithm to analyze a very large set of medical data in order to find new ways to treat diseases. They may also look for patterns in traffic data to help clear accidents faster.

Robotics . Some computer and information research scientists study how to improve robots. Robotics explores how a machine can interact with the physical world. Computer and information research scientists create the programs that control the robots. They work closely with engineers who focus on the hardware design of robots. Together, these workers test how well the robots do the tasks they were created to do, such as assemble cars or collect data on other planets.

Programming . Computer and information research scientists design new programming languages that are used to write software. The new languages make software writing more efficient by improving an existing language, such as Java, or by making a specific aspect of programming, such as image processing, easier.

Work Environment for Computer and Information Research Scientists [ About this section ] [ To Top ]

Computer and information research scientists hold about 33,500 jobs. The largest employers of computer and information research scientists are as follows:

Some scientists collaborate with engineers or other specialists or research scientists in different locations and do much of their work online.

Computer and Information Research Scientist Work Schedules

Most computer and information research scientists work full time.

How to Become a Computer or Information Research Scientist [ About this section ] [ To Top ]

Get the education you need: Find schools for Computer and Information Research Scientists near you!

Most jobs for computer and information research scientists require a master's degree in computer science or a related field. In the federal government, a bachelor's degree may be sufficient for some jobs.

Education for Computer and Information Research Scientists

Most computer and information research scientists need a master's degree in computer science or a related field, such as computer engineering. A master's degree usually requires 2 to 3 years of study after earning a bachelor's degree in a computer-related field, such as computer science or information systems.

Computer scientists who work in a specialized field may need knowledge of that field. For example, those working on biomedical applications may need to have taken some biology classes.

Advancement for Computer and Information Research Scientists

Some computer scientists may become computer and information systems managers .

Important Qualities for Computer and Information Research Scientists

Analytical skills. Computer and information research scientists must be organized in their thinking and analyze the results of their research to formulate conclusions.

Communication skills. Computer and information research scientists must communicate well with programmers and managers and be able to clearly explain their conclusions to people with no technical background. They often present their research at conferences.

Critical-thinking skills. Computer and information research scientists work on many complex problems.

Detail oriented. Computer and information research scientists must pay close attention to their work, because a small programming error can cause an entire project to fail.

Ingenuity. Computer and information research scientists must continually come up with innovative ways to solve problems, particularly when their ideas do not initially work as intended.

Logical thinking. Computer algorithms rely on logic. Computer and information research scientists must have a talent for reasoning.

Math skills. Computer and information research scientists must have knowledge of advanced math and other technical topics that are critical in computing.

Computer and Information Research Scientist Salaries [ About this section ] [ More salary/earnings info ] [ To Top ]

The median annual wage for computer and information research scientists is $131,490. The median wage is the wage at which half the workers in an occupation earned more than that amount and half earned less. The lowest 10 percent earned less than $74,210, and the highest 10 percent earned more than $208,000.

The median annual wages for computer and information research scientists in the top industries in which they work are as follows:

Job Outlook for Computer and Information Research Scientists [ About this section ] [ To Top ]

Employment of computer and information research scientists is projected to grow 21 percent over the next ten years, much faster than the average for all occupations.

About 3,300 openings for computer and information research scientists are projected each year, on average, over the decade. Many of those openings are expected to result from the need to replace workers who transfer to different occupations or exit the labor force, such as to retire.

Employment of Computer and Information Research Scientists

The research and development conducted by computer and information research scientists turn ideas into technology. As demand for new and better technology grows, demand for computer and information research scientists will grow as well.

Rapid growth in data collection by businesses will lead to an increased need for data-mining services. Computer and information research scientists will be needed to write algorithms that help businesses make sense of very large amounts of data.

A growing emphasis on cybersecurity also should lead to new jobs because computer and information research scientists will be needed to find innovative ways to prevent potential cyberattacks. In addition, an increase in demand for software may increase the need for computer and information research scientists who create new programming languages to make software writing more efficient.

Careers Related to Computer and Information Research Scientists [ About this section ] [ To Top ]

Computer and information systems managers.

Computer and information systems managers, often called information technology (IT) managers or IT project managers, plan, coordinate, and direct computer-related activities in an organization. They help determine the information technology goals of an organization and are responsible for implementing computer systems to meet those goals.

Computer Hardware Engineers

Computer hardware engineers research, design, develop, and test computer systems and components such as processors, circuit boards, memory devices, networks, and routers.

Computer Network Architects

Computer network architects design and build data communication networks, including local area networks (LANs), wide area networks (WANs), and Intranets. These networks range from small connections between two offices to next-generation networking capabilities such as a cloud infrastructure that serves multiple customers.

Computer Programmers

Computer programmers write and test code that allows computer applications and software programs to function properly. They turn the program designs created by software developers and engineers into instructions that a computer can follow.

Computer Systems Analysts

Computer systems analysts, sometimes called systems architects, study an organization's current computer systems and procedures, and design solutions to help the organization operate more efficiently and effectively. They bring business and information technology (IT) together by understanding the needs and limitations of both.

Database Administrators

Database administrators (DBAs) use specialized software to store and organize data, such as financial information and customer shipping records. They make sure that data are available to users and secure from unauthorized access.

Data Scientists

Data scientists use analytical tools and techniques to extract meaningful insights from data.

Information Security Analysts

Information security analysts plan and carry out security measures to protect an organization's computer networks and systems. Their responsibilities are continually expanding as the number of cyberattacks increases.

Network and Computer Systems Administrators

Computer networks are critical parts of almost every organization. Network and computer systems administrators are responsible for the day-to-day operation of these networks.

Software Developers

Software developers are the creative minds behind computer programs. Some develop the applications that allow people to do specific tasks on a computer or another device. Others develop the underlying systems that run the devices or that control networks.

Web Developers

Web developers design and create websites. They are responsible for the look of the site. They are also responsible for the site's technical aspects, such as its performance and capacity, which are measures of a website's speed and how much traffic the site can handle. In addition, web developers may create content for the site.

Top Executives

Top executives devise strategies and policies to ensure that an organization meets its goals. They plan, direct, and coordinate operational activities of companies and organizations.

More Computer and Information Research Scientist Information [ About this section ] [ To Top ]

For more information about computer and information research scientists, visit

Association for Computing Machinery

IEEE Computer Society

For information about opportunities for women pursuing information technology careers, visit

National Center for Women & Information Technology

A portion of the information on this page is used by permission of the U.S. Department of Labor.

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Computer or Information Research Scientist

Computer and information research scientists design innovative uses for new and existing technology. They study and solve complex problems in computing for business, science, medicine, and other fields.

Computer and information research scientists typically do the following:

Explore problems in computing and develop theories and models to address those problems
Collaborate with scientists and engineers to solve complex computing problems
Determine computing needs and system requirements
Develop new computing languages, software systems, and other tools to improve how people work with computers
Design and conduct experiments to test the operation of software systems, frequently using techniques from data science and machine learning
Analyze the results of their experiments
Write papers for publication and present research findings at conferences

Computer and information research scientists create and improve computer software and hardware.

To create and improve software, computer and information research scientists work with algorithms: sets of instructions that tell a computer what to do. Some difficult computing tasks require complex algorithms, which these scientists simplify to make computer systems as efficient as possible. These simplified algorithms may lead to advancements in many types of technology, such as machine learning systems and cloud computing.

To improve computer hardware, these scientists design computer architecture. Their work may result in increased efficiencies, such as better networking technology, faster computing speeds, and improved information security.

The following are examples of specialties for computer and information research scientists:

Programming. Some computer and information research scientists study and design new programming languages that are used to write software. New languages make software writing efficient by improving an existing language, such as Java, or by simplifying a specific aspect of programming, such as image processing.

Robotics . These scientists study the development and application of robots. They explore how a machine can interact with the physical world. For example, they may create systems that control the robots or design robots to have features such as information processing or sensory feedback.

Some computer and information research scientists work on multidisciplinary projects with electrical engineers, computer hardware engineers, and other specialists. For example, robotics specialists and engineers who design robots’ hardware may team up to test whether the robots complete tasks as intended.

Computer and information research scientists held about 33,500 jobs in 2021. The largest employers of computer and information research scientists were as follows:

Some scientists collaborate with engineers or other specialists or research scientists in different locations and do much of their work online.

Work Schedules

Most computer and information research scientists work full time.

Computer and information research scientists typically need at least a master’s degree in computer science or a related field. In the federal government, a bachelor’s degree may be sufficient for some jobs.

Computer and information research scientists typically need a master’s or higher degree in computer science or a related field, such as computer engineering. A master’s degree usually requires 2 to 3 years of study after earning a bachelor’s degree in a computer-related field, such as computer science or information systems. Some employers prefer to hire candidates who have a Ph.D. Others, such as the federal government, may hire candidates who have a bachelor’s degree in computer and information technology.

Computer and information research scientists who work in a specialized field may need knowledge of that field. For example, those working on biomedical applications may need to have studied biology.

Advancement

Some computer and information research scientists advance to become computer and information systems managers.

Computer and information research scientists typically have an interest in the Building, Thinking and Creating interest areas, according to the Holland Code framework. The Building interest area indicates a focus on working with tools and machines, and making or fixing practical things. The Thinking interest area indicates a focus on researching, investigating, and increasing the understanding of natural laws. The Creating interest area indicates a focus on being original and imaginative, and working with artistic media.

If you are not sure whether you have a Building or Thinking or Creating interest which might fit with a career as a computer and information research scientist, you can take a career test to measure your interests.

Computer and information research scientists should also possess the following specific qualities:

Analytical skills. Computer and information research scientists must be organized in their thinking and analyze the results of their research to formulate conclusions.

Critical-thinking skills. Computer and information research scientists work on many complex problems.

Detail oriented. Computer and information research scientists must pay close attention to their work, because a small error can cause an entire project to fail.

Ingenuity. Computer and information research scientists must continually come up with innovative ways to solve problems, particularly when their ideas do not initially work as intended.

Logical thinking . Computer algorithms rely on logic. Computer and information research scientists must have a talent for reasoning.

Math skills. Computer and information research scientists must have knowledge of advanced math and other technical topics that are critical in computing.

The median annual wage for computer and information research scientists was $131,490 in May 2021. The median wage is the wage at which half the workers in an occupation earned more than that amount and half earned less. The lowest 10 percent earned less than $74,210, and the highest 10 percent earned more than $208,000.

In May 2021, the median annual wages for computer and information research scientists in the top industries in which they worked were as follows:

Employment of computer and information research scientists is projected to grow 21 percent from 2021 to 2031, much faster than the average for all occupations.

For more information about computer and information research scientists, visit

Association for Computing Machinery

Computing Research Association

IEEE Computer Society

For information about opportunities for women pursuing information technology careers, visit

National Center for Women & Information Technology

To find job openings for computer and information research scientists in the federal government, visit

Where does this information come from?

The career information above is taken from the Bureau of Labor Statistics Occupational Outlook Handbook . This excellent resource for occupational data is published by the U.S. Department of Labor every two years. Truity periodically updates our site with information from the BLS database.

I would like to cite this page for a report. Who is the author?

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I think I have found an error or inaccurate information on this page. Who should I contact?

This information is taken directly from the Occupational Outlook Handbook published by the US Bureau of Labor Statistics. Truity does not editorialize the information, including changing information that our readers believe is inaccurate, because we consider the BLS to be the authority on occupational information. However, if you would like to correct a typo or other technical error, you can reach us at [email protected] .

I am not sure if this career is right for me. How can I decide?

There are many excellent tools available that will allow you to measure your interests, profile your personality, and match these traits with appropriate careers. On this site, you can take the Career Personality Profiler assessment, the Holland Code assessment, or the Photo Career Quiz .

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Example Career: Computer and Information Research Scientists

Career description.

Conduct research into fundamental computer and information science as theorists, designers, or inventors. Develop solutions to problems in the field of computer hardware and software.

What Job Titles Computer and Information Research Scientists Might Have

Computer Scientist
Control System Computer Scientist
Scientific Programmer Analyst

What Computer and Information Research Scientists Do

Analyze problems to develop solutions involving computer hardware and software.
Assign or schedule tasks to meet work priorities and goals.
Evaluate project plans and proposals to assess feasibility issues.
Apply theoretical expertise and innovation to create or apply new technology, such as adapting principles for applying computers to new uses.
Consult with users, management, vendors, and technicians to determine computing needs and system requirements.
Meet with managers, vendors, and others to solicit cooperation and resolve problems.
Conduct logical analyses of business, scientific, engineering, and other technical problems, formulating mathematical models of problems for solution by computers.
Develop and interpret organizational goals, policies, and procedures.
Participate in staffing decisions and direct training of subordinates.
Develop performance standards, and evaluate work in light of established standards.
Design computers and the software that runs them.
Maintain network hardware and software, direct network security measures, and monitor networks to ensure availability to system users.
Participate in multidisciplinary projects in areas such as virtual reality, human-computer interaction, or robotics.
Approve, prepare, monitor, and adjust operational budgets.

What Computer and Information Research Scientists Should Be Good At

Deductive Reasoning - The ability to apply general rules to specific problems to produce answers that make sense.
Inductive Reasoning - The ability to combine pieces of information to form general rules or conclusions (includes finding a relationship among seemingly unrelated events).
Problem Sensitivity - The ability to tell when something is wrong or is likely to go wrong. It does not involve solving the problem, only recognizing there is a problem.
Oral Comprehension - The ability to listen to and understand information and ideas presented through spoken words and sentences.
Written Comprehension - The ability to read and understand information and ideas presented in writing.
Oral Expression - The ability to communicate information and ideas in speaking so others will understand.
Fluency of Ideas - The ability to come up with a number of ideas about a topic (the number of ideas is important, not their quality, correctness, or creativity).
Information Ordering - The ability to arrange things or actions in a certain order or pattern according to a specific rule or set of rules (e.g., patterns of numbers, letters, words, pictures, mathematical operations).
Near Vision - The ability to see details at close range (within a few feet of the observer).
Category Flexibility - The ability to generate or use different sets of rules for combining or grouping things in different ways.

What Computer and Information Research Scientists Should Be Interested In

Investigative - Investigative occupations frequently involve working with ideas, and require an extensive amount of thinking. These occupations can involve searching for facts and figuring out problems mentally.
Realistic - Realistic occupations frequently involve work activities that include practical, hands-on problems and solutions. They often deal with plants, animals, and real-world materials like wood, tools, and machinery. Many of the occupations require working outside, and do not involve a lot of paperwork or working closely with others.
Artistic - Artistic occupations frequently involve working with forms, designs and patterns. They often require self-expression and the work can be done without following a clear set of rules.
Conventional - Conventional occupations frequently involve following set procedures and routines. These occupations can include working with data and details more than with ideas. Usually there is a clear line of authority to follow.

What Computer and Information Research Scientists Need to Learn

Computers and Electronics - Knowledge of circuit boards, processors, chips, electronic equipment, and computer hardware and software, including applications and programming.
Mathematics - Knowledge of arithmetic, algebra, geometry, calculus, statistics, and their applications.
English Language - Knowledge of the structure and content of the English language including the meaning and spelling of words, rules of composition, and grammar.
Education and Training - Knowledge of principles and methods for curriculum and training design, teaching and instruction for individuals and groups, and the measurement of training effects.
Telecommunications - Knowledge of transmission, broadcasting, switching, control, and operation of telecommunications systems.
Design - Knowledge of design techniques, tools, and principles involved in production of precision technical plans, blueprints, drawings, and models.
Administration and Management - Knowledge of business and management principles involved in strategic planning, resource allocation, human resources modeling, leadership technique, production methods, and coordination of people and resources.
Engineering and Technology - Knowledge of the practical application of engineering science and technology. This includes applying principles, techniques, procedures, and equipment to the design and production of various goods and services.
Customer and Personal Service - Knowledge of principles and processes for providing customer and personal services. This includes customer needs assessment, meeting quality standards for services, and evaluation of customer satisfaction.
Communications and Media - Knowledge of media production, communication, and dissemination techniques and methods. This includes alternative ways to inform and entertain via written, oral, and visual media.

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Home / Online Master’s Degree Programs / Online Master’s in Data Science / Data Scientist Jobs for Graduates with a Master’s Degree / How to Become a Computer and Information Research Scientist

How to Become a Computer and Information Research Scientist How to Become a Computer and Information Research Scientist How to Become a Computer and Information Research Scientist

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In 1965, Intel co-founder Gordon Moore wrote a short article for Electronics magazine in which he stated his belief that processor capabilities were doubling every year. He revised his statement 10 years later, saying he believed processors would double in complexity every other year as a result of continually emerging technologies and the physical properties of computer chips and their components. That belief quickly became known as “Moore’s Law,” which simply says computers will double in performance capability every two years.

The industry consensus is that Moore’s law won’t persist beyond the 2020s, as the trend of shrinking transistors means they would eventually have to be smaller than individual molecules, which isn’t a real possibility in the near future. However, that doesn’t mean there won’t be more advancements in computing technology. It’s up to the next generation of computer science experts to innovate and improve computers through programming, networking, materials, and research. These experts, often known as computer and information research scientists, work in many different industries, from biomedical engineering to sports analytics. Continue reading to learn more about how to become a computer and information research scientist, as well as the projected market and salary for this in-demand career.

Computer scientists working on computer hardware

What Does a Computer and Information Research Scientist Do?

Computer and information research scientists advance the field of computing technology through research and experimentation. As experts in how computers and network systems operate, they come up with new ways to program, assemble, and link computers and other devices. Their work improves processing, data transfer speeds, and more. They design experiments to test theories about new algorithms, programs, or systems and write research papers to be published in academic journals. They often work in data science, managing and protecting large data sets for governments or corporations. They may also work in computer system design or engineering firms, helping develop new software, systems, or programming languages.

Steps for Becoming a Computer and Information Research Scientist

Becoming a computer and information research scientist takes more than an interest in the inner workings of computers. It requires years of study, an advanced education, and an intricate knowledge of computer networks. Along the way, in the classroom and beyond, these tech experts pick up extensive experience working with computers in many different capacities.

Dive Into Computers

The most basic requirement for computer and information research scientists is a passion for computers. Even before getting out of high school, those interested in computer and information research can start to learn basic computer programming languages and functions, participating in school and extracurricular clubs where they might create basic software or build desktop computer systems. YouTube tutorials and other online learning materials also allow aspiring computer and information research scientists to work toward their goals independently.

Get the Right Education

Computer and information research scientists hold advanced degrees in their field. Their postsecondary educational path starts with a computer-related degree, such as a bachelor’s in data science or computer science. These programs teach important skills in programming, statistics, machine learning, and predictive modeling. To become a computer and information research scientist, aspiring professionals also need to complete a postgraduate degree, such as Maryville University’s online Master’s in Data Science . In this program, students build on their undergraduate education with courses in data mining, big data analytics, deep learning, and experimental design. Courses at an advanced level take skills earned in a bachelor’s degree program to the next level. At Maryville University, for example, master’s in data science students learn how to conduct the research and data analysis necessary to become a scientist in this field.

Earn Certifications

Many of the world’s top technology and computing corporations have their own industry certifications, which data scientists can earn to illustrate their capabilities to employers. Dell, IBM, Microsoft, and SAS offer some of the more popular ones.

Computer and Information Research Scientist Salaries

The U.S. Bureau of Labor Statistics (BLS) reports the median annual salary for computer and information research scientists was $118,370 per year as of May 2018, while the top 10% earned approximately $183,820 annually. The highest-paying industry by median annual salary was software publishing ($140,220), followed by research in the physical, engineering, and life sciences ($128,570) and computer systems design and related services ($124,220).

Employment Outlook for Computer and Information Research Scientists

As of May 2018, according to the BLS, there were 31,700 computer and information research scientist jobs in the United States. The BLS expects that number to reach 37,000 jobs by 2028 — a 16% growth rate, which is more than three times the national job market growth rate during the same period. The largest area of growth will be in computer systems design and related jobs, with 2,800 of the 5,200 new jobs added in that area. Scientific research and development services (1,200 jobs) will also see significant growth.

Learn More About How to Become a Computer and Information Research Scientist

Computer experts who want to take their knowledge of hardware, software, and programming to the next level should consider pursuing the education, experience, and certification required to become a computer and information research scientist. The field is growing, and innovators are needed to meet the demand for development in many industries. Discover how Maryville University’s online Master’s in Data Science can help you take the next step.

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How to Become a Computer Scientist

By Ajoke Aminu

Published: March 6, 2024

Do you dream of becoming the next Bill Gates? Well, becoming a computer scientist might just be the path for you, as we live in a world where technology is increasingly important, yet many feel overwhelmed by it and unable to understand the basics. Fortunately, this article provides easy-to-understand explanations for the fundamentals of computer science that gets you ahead in tech.

Career Summary

Computer scientist salary.

According to recent studies, the average computer scientist salary in the United States is a whopping US$94,337– not your average 9-to-5 paycheck! But wait, it gets even better as you scale:

Entry Salary (US$94k)
Median Salary (US$117k)
Executive Salary (US$164k)

To put that into perspective, the average income for a US citizen is around US$60,000 per year, meaning Computer Scientists are making almost double the average American’s salary!

What does a Computer Scientist do?

A computer scientist, for starters, is responsible for designing and implementing the software and hardware systems that power our digital world. Think of them as the superheroes of the cyberworld– the ones who ensure that your favorite apps run smoothly, your emails are delivered securely, and your devices stay free of pesky programs that threaten their functionality. From solving complex mathematical equations to debugging faulty code, computer and information research scientists are experts in all things digital.

Computer Scientist Career Progression

Entry-Level Positions: Computer scientists often begin their careers in entry-level roles such as software developer , programmer, or data analyst . These positions allow them to gain practical experience and apply their foundational knowledge.
Mid-Level Positions: After gaining a few years of experience, computer scientists can advance to mid-level positions such as software engineer, data scientist , or systems analyst. They take on more complex responsibilities, work on larger projects, and may start leading small teams.
Senior-Level Positions: With significant experience and expertise, computer scientists can move into senior-level positions like senior software architect , data science manager, or technical lead. In these roles, they have greater responsibilities, mentor junior team members, make strategic decisions, and may oversee multiple projects.
Specialization or Management Roles: As computer scientists progress in their careers, they may choose to specialize in a specific area of computer science, such as artificial intelligence, cybersecurity, or cloud computing. Alternatively, they can transition into management roles like IT project manager , technology director, or research scientist, where they oversee teams, budgets, and strategic initiatives.
Leadership or Executive Positions: With extensive experience and demonstrated leadership skills, computer scientists can advance to executive positions such as Chief Technology Officer (CTO), Chief Information Officer (CIO), or technology consultant. In these roles, they provide strategic direction, drive innovation, and make high-level decisions that impact the organization’s technology landscape.

Computer scientists are in high demand across various industries, providing a wide range of job opportunities and career advancement prospects.
Due to the demand for their skills, computer scientists often enjoy competitive salaries and attractive compensation packages.
Computer scientists have the opportunity to work on cutting-edge technologies and contribute to technological advancements, fostering innovation and creativity.
Many computer science roles offer flexible work arrangements, such as remote work options, flexible hours, and location independence, providing a better work-life balance.
Computer science is a dynamic field, requiring professionals to engage in continuous learning. This keeps their skills up-to-date and allows for ongoing growth and development.
The field of computer science evolves rapidly, requiring professionals to constantly adapt to new technologies, programming languages, and industry trends.
Computer scientists often face tight deadlines and high-pressure situations, especially when working on critical projects or dealing with complex technical challenges.
The fast-paced nature of the field and the need for technical expertise can lead to high expectations from employers and clients, requiring computer scientists to consistently perform at a high level.

Most Important Computer Scientist Skills

Programming and Coding
Network and Security
Mathematics and Algorithms
Data Structures
Software Development Methodologies

Popular Computer Scientist Specialization

Artificial Intelligence (AI) and Machine Learning: This specialty focuses on developing algorithms and models that enable computers to simulate intelligent behavior. Computer scientists in this field work on tasks like natural language processing, computer vision, robotics, and predictive modeling.
Data Science and Analytics: Data scientists specialize in extracting insights and valuable information from large datasets. They use statistical analysis, machine learning, and data visualization techniques to uncover patterns, trends, and correlations that can drive informed decision-making.
Cybersecurity: With the increasing prevalence of cyber threats, computer scientists specializing in cybersecurity play a critical role in protecting computer systems, networks, and data from unauthorized access, breaches, and other security risks. They develop security protocols, perform risk assessments, and implement measures to safeguard digital assets.
Software Engineering: Software engineers focus on designing, developing, and maintaining software systems. They apply engineering principles to create robust, scalable, and efficient software solutions for various purposes, including web and mobile applications, operating systems, and enterprise software.
Computer Networks and Systems: Computer scientists specializing in networks and systems design and maintain the infrastructure that allows computers to communicate and share resources. They work on tasks such as network architecture, network security, cloud computing, and distributed systems.

How to become a Computer Scientist

Considering a future in tech can be mind-boggling without the right guidance, especially as a computer scientist. We are here to hold you by the hands as you take the leap into the exciting world of computer science. In this guide, you will find the key steps you need to take to become the next tech superstar.

Getting a Tech Education

Is a computer science degree required.

No, you do not necessarily need a degree to become a computer scientist . Regardless, it is still relevant. While a formal degree in computer science or a related field can provide a strong foundation and open up opportunities, it is not the only path to a successful career in computer science.

So, why should I get a Computer Science degree?

Several businesses are more likely to interview candidates with a reasonable degree of education, which is highlighted even in the computer scientist job description.

Despite the possibility to succeed without a computer science degree , it is essential to consider these factors before deciding not to obtain one:

Foundational Knowledge: A degree program provides a structured curriculum that covers essential concepts, theories, and principles of computer science. It offers a comprehensive understanding of algorithms, data structures, programming languages, software development, computer architecture, and other core topics. This foundational knowledge forms a solid base for a career in computer science.
Specialized Education: A degree program allows you to specialize in specific areas of computer science based on your interests and career goals. You can choose elective courses or concentrate on fields like artificial intelligence, cybersecurity, software engineering, database systems, or computer graphics. Specialization can give you an advantage in the job market and open up opportunities in specific industries or research areas.
Credibility and Validation: A degree serves as tangible proof of your dedication, commitment, and expertise in the field. Employers often value a degree as it demonstrates that you have undergone a rigorous academic program and acquired a certain level of knowledge and skills. It can help you stand out among other candidates, especially in competitive job markets.
Career Advancement: Some roles in the field, particularly in research or academia, may require an advanced degree, such as a Master’s or Ph.D. Having a bachelor’s degree in computer science can be a stepping stone toward pursuing higher education and advancing your career in specialized areas.

What is the typical duration to earn a degree in Computer Science?

If you are wondering how long it will take before you can officially call yourself a computer scientist, the answer is not as simple as a one-size-fits-all approach.

Depending on the program you choose you should earn various degrees in the following timelines:

Bachelor’s Degree: A traditional undergraduate degree in computer science, such as a Bachelor of Science (B.S.) or a Bachelor of Arts (B.A.), typically takes around four years to complete. This duration assumes full-time enrollment and successful completion of all required courses.
Accelerated Bachelor’s Degree: Some universities offer accelerated programs that allow motivated students to complete their bachelor’s degree in a shorter timeframe, often in three years . These programs often involve heavier course loads, summer semesters, or credit for prior learning.
Master’s Degree: A Master of Science (M.S.) in computer science typically takes about two years to complete after earning a bachelor’s degree. This duration may vary depending on whether the program is pursued on a full-time or part-time basis.
Ph.D. Degree: A Doctor of Philosophy (Ph.D.) in computer science is a research-focused degree that can take anywhere from four to six years or more to complete. The duration depends on the student’s research progress, the complexity of the research topic, and other factors specific to the individual’s work.

Financial Commitments Involved in Studying Computer Science at University

Have you ever found yourself hovering over the “enroll” button for a Computer Science program, only to hesitate because you’re unsure of the costs? Although the cost of tuition for computer science programs at universities in the United States varies, this estimate can guide you.

On average, for the 2021-2022 academic year, the tuition fees for computer science degrees were approximately $13,300 for in-state students attending public universities and $46,497 for out-of-state students .

Additionally, you must remember to consider other expenses such as room and board, books and supplies, technology and equipment, and miscellaneous. To get an accurate estimate of the total cost, it’s recommended to visit the websites of specific universities you are interested in or contact their financial aid offices. Lastly, it’s also worth mentioning that computer science financial aid, scholarships, and grants can help offset the cost of studying.

Can I earn my Computer Science Degree Through Online Learning?

Yes, it is possible to become a computer scientist through online education . Some forms of online learning include:

Self-study: There are abundant online resources, tutorials , and courses available that can help you learn computer science concepts and programming languages. Platforms like Coursera and Udemy offer a wide range of courses from reputable institutions and instructors.
Bootcamps: Coding bootcamps are intensive, short-term training programs designed to teach specific programming skills. They often focus on practical application and hands-on experience, preparing students for specific roles in the industry. Bootcamps are typically shorter and more focused than traditional degrees.
Open-source contributions and projects: Engaging with open-source projects allows you to collaborate with other developers, build a portfolio, and demonstrate your skills to potential employers. Contributing to open-source projects can be a valuable learning experience and a way to showcase your abilities.
Certifications: Industry-recognized certifications, such as those offered by organizations like Microsoft , Cisco , or AWS , can demonstrate your expertise in specific areas of computer science and increase your job prospects.

Alternative Web Resources to Learn Computer Science Skills

Whether you’re a beginner looking to dip your toes into the world of computer science or a seasoned professional seeking new areas to explore, there’s no better time to start utilizing these invaluable web resources:

Codecademy : Codecademy focuses on interactive coding tutorials for different programming languages, including Python, JavaScript, HTML/CSS, and more. It provides a hands-on learning experience with real-time code editors and exercises.
FreeCodeCamp : FreeCodeCamp is an interactive platform that offers coding challenges and projects to help you learn web development and other computer science skills. It covers topics like HTML, CSS, JavaScript, and various frameworks.
Stack Overflow : Stack Overflow is a popular online community for programmers where you can ask questions, find answers, and engage in discussions related to computer science and programming. It’s a valuable resource for troubleshooting, gaining insights, and connecting with other developers.
GitHub : GitHub is a code hosting platform that also serves as a learning resource. You can explore open-source projects, collaborate with others, and contribute to existing projects to improve your coding skills and gain real-world experience.

8 Essentials Skills Needed to Become a Professional Computer Scientist

Programming: Proficiency in programming languages is fundamental for computer and information research scientists. You will learn how to write efficient and maintainable code, understand data structures and algorithms, and develop software solutions to solve problems.
Algorithm Design and Analysis: You will learn how to design and analyze algorithms, which are step-by-step procedures for solving computational problems. This skill is essential for optimizing performance, understanding efficiency, and evaluating trade-offs in algorithmic solutions.
Data Structures: Understanding data structures is crucial for organizing and manipulating data efficiently. Computer and information research scientists will learn about arrays, linked lists, stacks, queues, trees, graphs, and other data structures that facilitate effective data management and retrieval.
Software Development: Computer scientists gain expertise in software development methodologies and practices. This includes understanding the software development life cycle, version control, debugging techniques, testing strategies, and writing maintainable and scalable code. It is one of the most common skill requirements in computer scientist job description.
Computer Architecture: You will learn about computer organization and architecture, understanding the hardware components, memory systems, and how software interacts with the underlying hardware infrastructure. This knowledge is valuable for optimizing software performance.
Artificial Intelligence and Machine Learning: With the increasing influence of AI and machine learning, computer scientists often delve into these areas. You can gain skills in building and training models, data analysis, pattern recognition, and developing intelligent systems. AI is also another commonly required skill in a computer scientist job description.
Database Systems: Understanding database management systems is important for handling data storage, retrieval, and manipulation. You will learn about structured query language (SQL), relational database design, normalization, and working with database systems efficiently.
Networking and Security: Computer scientists often acquire knowledge of computer networks, network protocols, and security fundamentals. This includes understanding network architectures, protocols, encryption, and implementing measures to protect systems and data.

Practical Experience in Computer Science: Employment, Internship & Job Opportunities

Computer and information research scientists are in luck when it comes to practical experience because there are countless internship and job opportunities out there waiting for you. These chances will give you the opportunity to work on exciting projects, utilize cutting-edge technology, and develop crucial professional skills and network. Interestingly, the computer science industry is not slowing down anytime soon, so there’s no better time to jump on board and start gaining some hands-on experience.

Internship Opportunities for a Computer Scientist Across Different Niches

Software Development Internship : Many companies offer internships focused on software development, where you can work on real-world projects, collaborate with experienced developers, and gain practical coding skills. These internships may involve front-end or back-end development, mobile app development, or working with specific programming languages and frameworks.
Data Science and Analytics Internship : I nternships in data science and analytics involve working with large datasets, performing data analysis, applying machine learning techniques, and extracting insights. This can be in industries like finance, healthcare, e-commerce, or any field that relies on data-driven decision-making.
Cybersecurity Internship : With the increasing importance of cybersecurity, internships in this field provide opportunities to learn about and contribute to securing computer systems, networks, and data. You may work on tasks like vulnerability assessments, threat analysis, implementing security measures, or participating in incident response.
Artificial Intelligence and Machine Learning Internship : Internships in AI and machine learning allow you to work on projects related to natural language processing, computer vision, recommendation systems, or other AI applications. You may get hands-on experience with training models, working with data, and developing AI-based solutions.
Web Development and UI/UX Design Internship : These internships focus on designing and developing user-friendly websites, web applications, and user interfaces. You may gain experience in front-end development using HTML, CSS, JavaScript, and frameworks like React or Angular. UI/UX design internships involve creating intuitive and visually appealing user interfaces.
IT and Systems Internship : Internships in IT departments allow you to gain experience in managing computer systems, troubleshooting hardware or software issues, setting up networks, or working on infrastructure projects. This can be in organizations of various sizes, from startups to large enterprises.
Gaming and Virtual Reality Internship : Internships in the gaming industry involve game development, graphics programming, virtual reality (VR), or augmented reality (AR) projects. Computer and information research scientists may work on designing game mechanics, creating game assets, or implementing VR/AR experiences.

Top 10 High-demand Job Opportunities for Computer Science Experts

In the fast-paced world of technology, computer science experts are in high demand for roles, such as:

Software Developer/Engineer
Data Scientist/Analyst
Artificial Intelligence/Machine Learning Engineer
Cybersecurity Analyst/Engineer
Systems Analyst/Architect
Database Administrator
IT Project Manager
Research Scientist
User Experience/User Interface (UX/UI) Designer
Technical Consultant

Industries and Companies That Hire Computer Scientists

Technology Companies
Software Development Companies
IT Consulting Firms
Financial Institutions
Healthcare Organizations
Government Agencies
Research Institutions
Academic Institutions
E-commerce Companies
Entertainment Industry (gaming, animation, etc.)
Telecommunications Companies
Manufacturing Companies with a Focus on Technology
Transportation and Logistics Companies
Energy and Utility Companies
Defense and Security Organizations
Digital Marketing Agencies
Media and Broadcasting Companies

Finding a Balance in the Life of a Computer Scientist

Computer scientists typically enjoy great work arrangements with remote options, flexible hours, and location independence, promoting better personal commitment management and work-life balance. Their schedules can adapt to optimize productivity, although project demands may require additional hours during critical phases.

Essentially, finding remote work opportunities provide autonomy, reduced commuting, and increased work-life balance. The project-based nature of their work allows for breaks and downtime between milestones, supporting work-life balance. Company culture plays a role as well, with organizations prioritizing work-life balance through policies, initiatives, and a supportive environment.

Most importantly, personal time management, effective task prioritization, and setting boundaries contribute to maintaining balance, while continuous learning and skill development strike a harmony between work-related and personal interests, fostering a well-rounded lifestyle.

What’s the Career Outlook for Computer Scientist?

With the rapid advancement of technology and digital transformation across industries, there is a consistently high demand for skilled computer and information research scientists. Computer and information research scientists can anticipate a 21% increase from 2021 to 2031, which is higher compared to the average percentage of other professions.

Thus, there will be approximately 3,300 computer and information research scientists job openings per year over the next decade. The competitive computer scientist salary, entrepreneurial prospects, and global demand make computer science an attractive field. Overall, the career outlook for computer scientists is promising, with ample opportunities for growth, innovation, and contribution to society.

Computer Scientist Popular Career Specialties

Should I become a Computer Scientist?

Deciding whether to become a computer scientist is not a trivial matter and requires careful consideration of many factors. After reading this article, you now have a better idea of what the field entails, what skills you need, and what opportunities you can pursue. But don’t let the facts alone sway your decision.

Remember that your personal interests, passions, and strengths should also come into play. Are you a problem solver at heart? Do you enjoy learning new technologies and tools? Do you like working in teams or on your own? These are some of the questions you should ask yourself before committing to a career in computer science.

Once you’ve made up your mind, keep in mind that your long-term goals and aspirations can help you navigate the ever-changing landscape of the tech industry. Whether you want to start your own business, work for a non-profit, or pursue a Ph.D., the knowledge and skills you acquire as a computer scientist can open up many doors and opportunities. So, be confident and stay curious!

Careers Related to Computer Scientist

Computer Programmer
Data Analyst
Information Technology Manager
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Home / Careers / Computer Scientist

What is a Computer Scientist?

As a practice, computer science applies theoretical expertise to real-world problems in order to develop more efficient technologies. This involves designing computer software, developing information technology and improving computer hardware.

More broadly, computer science is the study of how computers can solve a wide range of problems. This field integrates topics from mathematics, physics, engineering and design.

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Among these topics, computer scientists explore computational complexity theory as well as the theory and design of programming languages. These theories focus on examining how computers can be used to complete tasks more efficiently. This requires an understanding of the foundations of computer science such as formal logic, cryptography and probability theory. While these topics are often abstract, they have real-world applications. Research from these fields enables and strengthens the technology we use on a daily basis.

Throughout their careers, computer scientists develop theoretical expertise that they can creatively apply to new problems like algorithm development. At the same time, an understanding of practical software tools and patterns can help them build interpretable code. Finally, application domain knowledge can aid them in effectively addressing any problems that arise.

Computer scientists have many options for computer science careers . Computer scientists may be employed by software companies and research institutions. However, the widespread use of computers means computer scientists work in many diverse fields.

What Does a Computer Scientist Do?

The role of a computer scientist is to apply concepts from computer science to create efficient solutions. However, the goals and responsibilities of a computer scientist vary depending on the organization or job.

In academia, computer scientists may focus on expanding computational theory as well as educating the next generation of computer scientists. Meanwhile, computer scientists in various other industries focus on finding ways to improve efficiency of real-world computer systems.

Working alongside computer engineers and software engineers, computer scientists effectively communicate their work to these teams, as well as to non-technical stakeholders.

College of Engineering and Computer Science

How to think like a computer scientist.

The book “ How to Think Like a Computer Scientist ” is a guide to the basics of programming and computational thinking. It is an open source resource published under the GNU Free Documentation License. This means it is freely available to anyone interested in learning the basics of computer science. It is a useful resource and a starting point to learn the essentials of computer science.

“How to Think Like a Computer Scientist” is not only a guide to the Python programming language, but to many essential concepts of computer science like the theory of computation. Additional areas this book dives into include:

How computer programs work
Object-oriented programming
What a programming language is and the essential components such as syntax, variables, conditionals, iteration and more

Computer Scientist Skills

When it comes to core skills, computer science professionals should have the ability to measure and compare the efficiency of programs (which is called “analysis of algorithms”). A strong understanding of computer architecture, or how computers work, is also essential.

Additionally, computer scientists are familiar with various programming languages such as Python , C , Java and others. Computer scientists most likely have a passion for technology and enjoy learning about how computers work.

How to Become a Computer Scientist | 5 Steps

While there are different routes to becoming a computer scientist, aspiring professionals tend to follow some variation of this traditional trajectory: Earn a bachelor’s degree in computer science, pursue a master’s degree in computer science or engineering, find a specialization, consider a Ph.D. and eventually land their first computer or information research job.

While everyone’s goals and path to success can differ, computer scientists should be equipped with the proper education and practical experience. Learn more about how to launch your career and become a computer scientist below.

Earn a bachelor’s in computer science or related field

Aspiring computer scientists may begin their professional journey by earning their bachelor’s degree in computer science or a STEM-related field . Although topics may vary depending on the program or university, a bachelor’s degree in computer science typically involves courses in software engineering, computation theory, data structures and algorithms, programming languages and more.

While this foundational knowledge is important, learning how to become a computer scientist also means being attentive to an evolving industry. By learning key computer science concepts and adapting to a changing field, you may be better prepared to enter the workforce.

Earn a master’s degree in computer science or computer engineering

Once you have a bachelor’s degree in computer science, you already have a basic understanding of the field. However, individuals considering how to become a computer scientist typically need to pursue a master’s degree, according to the Bureau of Labor Statistics (BLS). This allows them to strengthen their expertise and potentially gain a competitive edge over their peers in the job market.

A master’s degree in computer science or a master’s degree in computer engineering build on the fundamentals and give aspiring computer scientists advanced knowledge of programming, discrete mathematics and computer systems. For many, pursuing a master’s degree in computer science online is a convenient option if you are unable to relocate or take time off from your existing job to earn a degree. Online programs often grant you flexibility in completing coursework on your own schedule.

Consider a specialization

On the path to become a computer scientist, many individuals find their niche by choosing a specialization that is more specific to their personal interests and career goals. Professionals can choose from specializations in artificial intelligence , game design, software engineering, computer-human interface and many more.

Choosing the right computer science specialization for you depends on your personal preference, technical experience and long-term career goals. Research different specializations in order to find one that interests you most.

Consider a Ph.D.

For computer scientists farther along in their career and even those planning ahead, a Ph.D. can grant a more comprehensive and advanced understanding of the field. In fact, some employers may require a Ph.D. in order for you to qualify for high-level roles.

This educational path may be suitable for professionals who are interested in a more research-oriented role or are eager to pursue a career in academia. Consider a Ph.D. program if you have a unique research interest.

Get your first computer scientist job

Prepared with knowledge, technical practice and research experience, computer scientists are well-positioned to begin searching for a job in their desired field of computer science.

With new job opportunities come networking communities and insight into how the industry is evolving rapidly. Computer scientists can apply their theoretical knowledge to real-world problems to create more efficient, helpful technology.

What is the Average Computer Scientist Salary?

Computer scientists generally earn above-average salaries. The median annual computer and information research scientist salary in 2020 was $126,830 , according to the BLS. Salary will vary by industry and employer.

Computer scientists are in high demand. The BLS estimates computer and information research science jobs in the United States will grow by 22% from 2020-2030 . This is well above the average growth rate for other careers.

With increasing utilization of computers in nearly every industry, this trend is expected to continue. Software development companies are continuing to grow and flourish. More industries than ever are integrating computer science concepts into their day to day.

Interested in a different career? Check out our bootcamp guides below:

Data Science Bootcamp Guide
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Last updated: September 2021

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What does a Computer Research Scientist do?

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Computer and information research scientists find new approaches to computing technology as well as studying and solving complex problems in computing for business, science, and other fields. They create and improve computer hardware and software and work at a more theoretical level than other computer professionals. Some computer and information research scientists specialize in computer languages as well as other specialities. Watch a video to learn what a computer research scientist does:

How to Become a Computer Research Scientist

An entry-level position as a computer and information research scientist may vary in education level depending on the industry. However, most employers look for candidates that hold at least a graduate degree (meaning a master’s degree). Some employers though may require a Ph.D. in computer science or a related field. A Ph.D. normally takes 4-5 years of further study after earning your bachelor’s degree in a related field like information systems or computer science. The federal government is the exact opposite, they may accept a candidate that holds a bachelor’s degree.

Once you earn your degree, you will need to gain experience. According to O*NET OnLine, employers may look for candidates that have at least five years of experience. At the same time, you will want to start specializing in an area of research. For instance, in biomedical applications, you may need to take biology classes. Several computer and information research scientists become secondary teachers and some may work with electrical engineers or computer hardware engineers. Other specialties in this career include data mining, robotics, and programming.

Job Description of a Computer Research Scientist

Computer and information research scientists have the duty of researching fundamental issues in computing and develop theories and models to address them. They help solve complex computer problems and some create programs to control robots. They have the task of inventing new computing tools, languages, and methods to help people work with computers in a more efficient way.

These scientists improve software systems and design experiments to test the effectiveness of their operation. They analyze experimental results and publish their findings in academic journals. They may also present the findings of their experiments at a conference. The work of computer and information research scientists may advance many types of technology like cloud computing and machine learning systems. He or she should have analytical, communication, and critical thinking skills, as well as be detail-oriented, logical thinking, and have ingenuity. Math skills would also be needed.

Computer Research Scientist Career Video Transcript

Developing the tools and technologies of tomorrow… requires hard work today. Computer and information research scientists invent new approaches to computing technology and improve the use of existing technology. They study complex computing problems and are often at the forefront of solving them for business, science, medicine, and other fields. These research scientists build algorithms or sets of instructions that tell a computer what to do. They may use an algorithm to develop a new computing language, create programs to control robots, and simplify the ways people interact with computers.

Their work often leads to technological advancements, such as better networking technology, faster computing speeds, and improved information security. In general, computer and information research scientists work at a more theoretical level than other computer professionals. Computer and information research scientists work for the federal government, computer systems design firms, research and development departments, and colleges and universities. Most positions are full time. Most computer and information research scientists need a master’s degree in computer science or a related field, such as computer engineering. For federal government jobs, a bachelor’s degree may be sufficient.

Article Citations

Bureau of Labor Statistics, U.S. Department of Labor, Occupational Outlook Handbook, Computer and Information Research Scientists .

National Center for O*NET Development. 15-1111.00. O*NET OnLine .

News Center

Pass or fail researchers grade progress of long-term cybersecurity goals.

Georgia Tech Cybersecurity and Privacy Professor Rich DeMillo

In November 2003, fifty of the nation’s top computer scientists met in the Virginia countryside to create a plan tackling the biggest problems facing the growing field of computer security and privacy, known then as trustworthy computing.

The meeting borrowed elements from the Gordon Research Conferences, meaning the discussions and attendees were never made public. It was the second in a series of highly nontraditional conferences meant to define important questions rather than present current research.

The grand challenges established by this group of academics drove the cybersecurity research agenda for over a decade.

Twenty-one years later, conference leaders Rich DeMillo , Georgia Tech professor and Charlotte B. and Roger C. Warren Chair in Computing, and Georgia Tech alumnus Eugene Spafford have collected feedback from the original participants and created a report on the progress made, and where they fell short.

“When we started the retrospective, we were all convinced that the whole exercise had been a failure,” said DeMillo. “But after some reflection, that judgment seemed too harsh.”

The rapid evolution of technology made it difficult to give each challenge a simple pass/fail grade, but the group was still able to highlight successes in their report. For example, DeMillo points out that global scale denial of service attacks never materialized because scientists figured out the right combination of policy, governance, and technology to make them ineffective at that scale.

“Context matters for when these challenges were issued,” said DeMillo. “We could not predict the new technologies and methods that sprang up over the years.”

The Official Report Card

In May 2023, twenty years after the first Grand Challenges meeting, DeMillo and Spafford reconvened the original participants for a retrospective at Purdue University’s Center for Education and Research in Information Assurance and Security. The meeting was to see how well the community had done in predicting the course of the field. In effect, they wanted to grade the work of the original Computing Research Association (CRA) conference.

Here’s the complete list and how today’s researchers grade the community’s progress:

Grand Challenge 1 : Within the decade, eradicate widespread viral, spam, and denial of service attacks.

Grade B- : Although global viral attacks have largely been avoided, ransomware, supply chain attacks, and malware that cripple important systems were not foreseen.

Grand Challenge 2 : Develop the scientific principles, tools, and development methods for building large-scale systems to operate critical infrastructure, support democratic institutions, and further significant societal goals, ensuring their trustworthiness even though they are appealing targets.

Grade F : Infrastructure protection has not received the same level of attention as IT, and as a result, critical systems, from electrical power grids to electronic voting systems, remain vulnerable to foreign and domestic threats.

Grand Challenge 3 : For the coming dynamic, ubiquitous computing systems and applications, create an overall framework to provide end users with comprehensible security and privacy that they can manage.

Grade D : Usable security is still an elusive goal, and a unified approach to privacy protection in the U.S. lags most developed countries.

Grand Challenge 4 : In the next ten years, aim to create and implement quantitative models, methods, and tools for managing information systems risks that are on par with quantitative financial risk management techniques.

Grade Incomplete : The economics of cybersecurity remains unexplored. From board rooms to kitchen tables, cybersecurity customers still do not know how much protection they get for every dollar spent on cybersecurity products.

Highlighting the Successes

Despite advancing technology creating a moving target for researchers, the framework laid out by DeMillo and the CRA committee has been a baseline for security research for the past twenty years.

“The National Science Foundation, DARPA, the Department of Homeland Security, and others reflected on these challenges when they considered new research proposals,” said DeMillo. “The 2003 conference laid an important foundation for scientific growth.”

This growth created a ripple effect across “generations” of academic researchers. When the students of DeMillo and his colleagues graduated, they began advising students of their own or guiding Fortune 500 companies through the pitfalls of an ever-changing cyber landscape. Either way, these graduates confronted the challenges defined by their mentors while adapting to new ones.

“The growth of cybersecurity academic programs like the ones we offer at SCP are directly traceable to the skills gaps that the grand challenges exposed,” he added. “And new fields like the security of engineered systems being invented here and elsewhere, are novel ways to approach the problem of systems that society can trust.”

What are the Grand Challenges to Cybersecurity Now?

According to DeMillo, those questions need to be defined by the researcher leaders of today.

“The 2003 report was a milestone, but I hope there will be a cohort of young scientists who will lay out new grand challenges and how to confront them,” he said.

As he points out in a report published on the CRA website, topics like AI, side-channel attacks, blockchain, and quantum computing are just a few of the emerging subfields with the potential to define the next 20 years of cybersecurity research.

More Information on the Original Conference

In 2002, the CRA sponsored its first Grand Research Challenges in Computer Science and Engineering . This was the first in a series of highly non-traditional conferences where the goal was to define important questions rather than expose current research. Grand challenges meetings sought out-of-the-box thinking to expose some of the exciting, deep challenges yet to be met in computing research.

Due to the importance and pressing needs for information security and assurance, CRA's second Grand Research Challenges Conference was devoted to defining technical and social challenges in information security and assurance.

The CRA and National Science Foundation tasked the conference- led by DeMillo, then dean of Georgia Tech's College of Computing, and Spafford- to define the biggest security problems facing the growing computing and communications infrastructure of the early 2000’s.

The resulting report Four Grand Challenges in Trustworthy Computing was released to the public in a ceremony at the National Press Club. It has become one of the pillars for research planners and policy-makers.

Additional information

How Much Research Is Being Written by Large Language Models?

New studies show a marked spike in LLM usage in academia, especially in computer science. What does this mean for researchers and reviewers?

research papers scroll out of a computer

In March of this year, a tweet about an academic paper went viral for all the wrong reasons. The introduction section of the paper, published in Elsevier’s Surfaces and Interfaces , began with this line: Certainly, here is a possible introduction for your topic.

Look familiar?

It should, if you are a user of ChatGPT and have applied its talents for the purpose of content generation. LLMs are being increasingly used to assist with writing tasks, but examples like this in academia are largely anecdotal and had not been quantified before now.

“While this is an egregious example,” says James Zou , associate professor of biomedical data science and, by courtesy, of computer science and of electrical engineering at Stanford, “in many cases, it’s less obvious, and that’s why we need to develop more granular and robust statistical methods to estimate the frequency and magnitude of LLM usage. At this particular moment, people want to know what content around us is written by AI. This is especially important in the context of research, for the papers we author and read and the reviews we get on our papers. That’s why we wanted to study how much of those have been written with the help of AI.”

In two papers looking at LLM use in scientific publishings, Zou and his team* found that 17.5% of computer science papers and 16.9% of peer review text had at least some content drafted by AI. The paper on LLM usage in peer reviews will be presented at the International Conference on Machine Learning.

Read Mapping the Increasing Use of LLMs in Scientific Papers and Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews

Here Zou discusses the findings and implications of this work, which was supported through a Stanford HAI Hoffman Yee Research Grant .

How did you determine whether AI wrote sections of a paper or a review?

We first saw that there are these specific worlds – like commendable, innovative, meticulous, pivotal, intricate, realm, and showcasing – whose frequency in reviews sharply spiked, coinciding with the release of ChatGPT. Additionally, we know that these words are much more likely to be used by LLMs than by humans. The reason we know this is that we actually did an experiment where we took many papers, used LLMs to write reviews of them, and compared those reviews to reviews written by human reviewers on the same papers. Then we quantified which words are more likely to be used by LLMs vs. humans, and those are exactly the words listed. The fact that they are more likely to be used by an LLM and that they have also seen a sharp spike coinciding with the release of LLMs is strong evidence.

Charts showing significant shift in the frequency of certain adjectives in research journals.

Some journals permit the use of LLMs in academic writing, as long as it’s noted, while others, including Science and the ICML conference, prohibit it. How are the ethics perceived in academia?

This is an important and timely topic because the policies of various journals are changing very quickly. For example, Science said in the beginning that they would not allow authors to use language models in their submissions, but they later changed their policy and said that people could use language models, but authors have to explicitly note where the language model is being used. All the journals are struggling with how to define this and what’s the right way going forward.

You observed an increase in usage of LLMs in academic writing, particularly in computer science papers (up to 17.5%). Math and Nature family papers, meanwhile, used AI text about 6.3% of the time. What do you think accounts for the discrepancy between these disciplines?

Artificial intelligence and computer science disciplines have seen an explosion in the number of papers submitted to conferences like ICLR and NeurIPS. And I think that’s really caused a strong burden, in many ways, to reviewers and to authors. So now it’s increasingly difficult to find qualified reviewers who have time to review all these papers. And some authors may feel more competition that they need to keep up and keep writing more and faster.

You analyzed close to a million papers on arXiv, bioRxiv, and Nature from January 2020 to February 2024. Do any of these journals include humanities papers or anything in the social sciences?

We mostly wanted to focus more on CS and engineering and biomedical areas and interdisciplinary areas, like Nature family journals, which also publish some social science papers. Availability mattered in this case. So, it’s relatively easy for us to get data from arXiv, bioRxiv, and Nature . A lot of AI conferences also make reviews publicly available. That’s not the case for humanities journals.

Did any results surprise you?

A few months after ChatGPT’s launch, we started to see a rapid, linear increase in the usage pattern in academic writing. This tells us how quickly these LLM technologies diffuse into the community and become adopted by researchers. The most surprising finding is the magnitude and speed of the increase in language model usage. Nearly a fifth of papers and peer review text use LLM modification. We also found that peer reviews submitted closer to the deadline and those less likely to engage with author rebuttal were more likely to use LLMs.

This suggests a couple of things. Perhaps some of these reviewers are not as engaged with reviewing these papers, and that’s why they are offloading some of the work to AI to help. This could be problematic if reviewers are not fully involved. As one of the pillars of the scientific process, it is still necessary to have human experts providing objective and rigorous evaluations. If this is being diluted, that’s not great for the scientific community.

What do your findings mean for the broader research community?

LLMs are transforming how we do research. It’s clear from our work that many papers we read are written with the help of LLMs. There needs to be more transparency, and people should state explicitly how LLMs are used and if they are used substantially. I don’t think it’s always a bad thing for people to use LLMs. In many areas, this can be very useful. For someone who is not a native English speaker, having the model polish their writing can be helpful. There are constructive ways for people to use LLMs in the research process; for example, in earlier stages of their draft. You could get useful feedback from a LLM in real time instead of waiting weeks or months to get external feedback.

But I think it’s still very important for the human researchers to be accountable for everything that is submitted and presented. They should be able to say, “Yes, I will stand behind the statements that are written in this paper.”

*Collaborators include: Weixin Liang , Yaohui Zhang , Zhengxuan Wu , Haley Lepp , Wenlong Ji , Xuandong Zhao , Hancheng Cao , Sheng Liu , Siyu He , Zhi Huang , Diyi Yang , Christopher Potts , Christopher D. Manning , Zachary Izzo , Yaohui Zhang , Lingjiao Chen , Haotian Ye , and Daniel A. McFarland .

Stanford HAI’s mission is to advance AI research, education, policy and practice to improve the human condition. Learn more .

Pass or Fail? Researchers Grade Progress of Long-Term Cybersecurity Goals