phd in engineering design

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Phd program.

The PhD in Human Centered Design & Engineering at the University of Washington provides unparalleled depth and experience for students interested in studying the conception, design, implementation, evaluation, and effects of technologies.

The University is located on a beautiful campus in the heart of the city of Seattle. HCDE is housed in the  College of Engineering , and benefits from the research tradition of a leading R1 research institution.

The HCDE doctoral program prepares students for careers as scholars and researchers through relevant coursework, mentorship from faculty , and collaboration with peers. Early in the program, students may explore different topics and research areas through  Directed Research Groups  and other independent projects. PhD students choose their dissertation adviser within their first year and begin to focus on a research area for their dissertation .

HCDE PhD Information Sessions

Hosted by HCDE PhD Program Director Sean Munson and Academic Services Director Kathleen Rascon, this information session is for prospective PhD students looking to apply the Department. 

Students in the HCDE PhD program complete a minimum of 90 credits of coursework and research as they progress toward degree completion. The first two years are primarily focused on academic course work as the foundation for ensuing research. The remainder of the program is focused on extensive research and program milestones. 

Applicants to the HCDE PhD program are required to apply to both the HCDE department and the UW Graduate School. The application deadline for the 2024-2025 academic year is November 30, 2023. 

Costs & Financing

Students are obligated to pay the associated tuition for courses they are enrolled in, but the department strives to fund all of its PhD students through Teaching Assistantships (TAs) and Research Assistantships (RAs). 

Faculty & Research

HCDE's award-winning, interdisciplinary  faculty  focus on six areas of research and teaching: influencing awareness, thinking, and behavior; design for emergent collaborations and organizations; low resource and underserved populations; material and embodied technologies, and ubiquitous computing; data visualization and big data; and learning in professional and technical environments. 

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Human-Centered Technology, Innovation & Design, Ph.D.

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Innovations in technologies redefine and reshape people's lives, changing social and cultural practices, norms and values, institutional processes, and economies and infrastructures. Working to develop new applications for existing and emerging human-centered technologies informed through rigorous, interdisciplinary research and managing socio-technical transitions is a fast-growing and highly important area of research across a number of fields and disciplines. The mission of the Tandon School of Engineering's Human-Centered Technology, Innovation & Design Ph.D. program is to educate and train scholars who will produce pioneering research and scholarship at the vanguard of technological practice and theory.

This program fosters student research through its focus on high-quality supervision and training by faculty members with significant research strengths in a diverse range of technology-related fields, including: digital media and creative practice, design and human-computer interaction, science and technology studies, urban and environmental studies, sociotechnical complex systems, and technology management and innovation. Students in the program typically follow an individualized path based in one of four main areas of focus:

• Human-Computer Interaction (HCI)
• Design Research & Practice
• Management Science
• Computational Social Science

The Human-Centered Technology, Innovation & Design program is a unique interdisciplinary Ph.D. program, offering a rigorous and flexible course of study that unites the strengths of the Departments of Technology Management and Innovation and Technology Culture & Society at the NYU Tandon School of Engineering. It is ideal for students who are primarily interested in pursuing teaching and/or research-based careers at higher education institutions. Universities with undergraduate and graduate programs that emphasize the integration of design and technology development with the critical study of society and technology or the management sciences are a primary source of career opportunities for our graduates. Similarly, government agencies, not-for-profit research organization, think tanks, corporate research centers, and research-based design and consulting firms also seek our graduates. 

Urban Science Doctoral Track

Admissions/applications requirements.

Admission to the Doctor of Philosophy in Human-Centered Technology, Innovation & Design program is based on an in-depth evaluation of the applicant’s academic record, professional experience, research potential, interest in doctoral study, and overall intellectual and professional qualifications. The GRE is optional, while proof of english language proficiency is required for international students.

Find out more about Admission Requirements and Graduate Admissions .

Degree Requirements and Curriculum

The curriculum for the Ph.D. in Human-Centered Technology, Innovation & Design Program fosters a research-intensive doctoral education relevant to understanding and shaping the impact of new technologies on a complex and rapidly-changing society and its institutions. We focus on how technology shapes and molds society and culture and how, in turn, social and cultural institutions respond to those impacts. 

The core coursework exposes students to advanced design and research skills modulated by the development of a critically reflexive understanding of the ways in which society and technology deeply influence design and development. Research methods courses help students develop advanced qualitative, quantitative, and practice-based research as the basis for inquiring into, designing, and evaluating new technologies in the service of society.

Thematic elective courses help students gain in-depth knowledge in a focused area related to the key themes of human-computer interaction, design research, and management science. Our faculty also specialize in several areas of focus: disability studies and inclusive design, citizen science, urban sustainability, design for social change, science and technology studies, design studies, and technology ethics and politics. Students and doctoral advisers work together to curate and develop a rigorous course of study in the program.

Students are required to complete 75 credits, including 51 credits from the course work, which includes doctoral seminars, research methods courses, and thematic electives, and 24 credits from the dissertation. For more information on specific faculty interests, please refer to the faculty pages under the relevant programs.

Research Training and Interaction with Faculty

Students are expected to work actively with one or more faculty each year, and focus on completing research. Students are strongly encouraged to present research in progress once a year and work towards publishable papers, usually with a faculty as co-author. Students are strongly encouraged to work with their primary advisors to outline a plan of study where they can be involved in institutional research. Every student participates in formal research seminars with departmental faculty and visitors.

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PhD Admissions

Earn your doctorate at duke.

Completing a PhD program in engineering is hard. Really hard. But after years of preparation, frustration and celebration, a Duke doctorate stands out from the crowd.

Between field-defining faculty and a web of industrial, entrepreneurial and public-policy connections, with a Duke Engineering PhD, you can just about go anywhere and do just about anything your heart desires.

And with Duke’s comprehensive financial and professional support, you won’t take that journey alone.

Duke: The Path to a High-Impact Career

Wherever your path leads you, a Duke PhD will ensure you’ll arrive prepared to make a difference.

Biomedical Engineering

Civil & Environmental Engineering

Electrical & Computer Engineering

Mechanical Engineering & Materials Science

Guaranteed funding.

Duke provides significant financial support. And that’s just the beginning. There’s mentorship and career exploration support, too.

Generous Stipend

Guaranteed pay, 12 months a year, for the first five years

Paid Tuition

Covered by Duke during the first five years of study

For the first five years, Duke pays all mandatory fees

Insurance Coverage

For six years, Duke pays your health and dental premiums

Applying to Duke

Contact us at [email protected]

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Review Financial Support Package

5 years of stipend—plus six years of health and dental coverage

Find Your Deadline

See the application calendar for all Duke PhD programs

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Using Duke’s secure online platform

Diversity Makes Better Engineers

An optimist sees the glass as half full. A pessimist? Half empty. An engineer sees a glass that’s twice as big as it needs to be. Point is, engineers see things differently. Duke engineers see things very differently. Why use glass at all? Can we create a more efficient material? Ooh, should we include a water quality sensor? Here, we value different backgrounds and ways of thinking—because new approaches generate new solutions.

PhD students

Phd students per tenure-track faculty member, of our phd students received an nsf or other prestigious fellowship, in new research awards won in fy22, best graduate biomedical engineering program.

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Lower cost of living in Durham vs. Boston

Facilities: welcome to wilkinson.

The newest of our buildings is 81,000 square feet of transformational design. Inside Wilkinson are research neighborhoods focused on advances in health, computing and the environment.

Dedicated workspaces for doctoral students feature natural light and campus views.

Durham and Beyond

Location. location. location..

At the north vertex of North Carolina’s famed Research Triangle, the city of Durham is essential to the Duke Engineering experience. Among our neighbors are hundreds of startups and standard bearers both private and public, a growing collection of James Beard Award-winning chefs, and a quickly growing community and skyline. River rafting, trail hiking, mountain climbing and sandy beaches are all just a couple hours’ drive away.

It doesn’t take an advanced degree to see why Durham is the #3 best place to live in America according to U.S. News and World Report, but come get one here anyway.

Interested in joining our community?

Start a conversation with Duke.

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Which program is right for you?

Through intellectual rigor and experiential learning, this full-time, two-year MBA program develops leaders who make a difference in the world.

A rigorous, hands-on program that prepares adaptive problem solvers for premier finance careers.

A 12-month program focused on applying the tools of modern data science, optimization and machine learning to solve real-world business problems.

Earn your MBA and SM in engineering with this transformative two-year program.

Combine an international MBA with a deep dive into management science. A special opportunity for partner and affiliate schools only.

A doctoral program that produces outstanding scholars who are leading in their fields of research.

Bring a business perspective to your technical and quantitative expertise with a bachelor’s degree in management, business analytics, or finance.

A joint program for mid-career professionals that integrates engineering and systems thinking. Earn your master’s degree in engineering and management.

An interdisciplinary program that combines engineering, management, and design, leading to a master’s degree in engineering and management.

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This 20-month MBA program equips experienced executives to enhance their impact on their organizations and the world.

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PhD Program

Program overview.

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Rigorous, discipline-based research is the hallmark of the MIT Sloan PhD Program. The program is committed to educating scholars who will lead in their fields of research—those with outstanding intellectual skills who will carry forward productive research on the complex organizational, financial, and technological issues that characterize an increasingly competitive and challenging business world.

Start here.

Learn more about the program, how to apply, and find answers to common questions.

Admissions Events

Check out our event schedule, and learn when you can chat with us in person or online.

Start Your Application

Visit this section to find important admissions deadlines, along with a link to our application.

Click here for answers to many of the most frequently asked questions.

PhD studies at MIT Sloan are intense and individual in nature, demanding a great deal of time, initiative, and discipline from every candidate. But the rewards of such rigor are tremendous:  MIT Sloan PhD graduates go on to teach and conduct research at the world's most prestigious universities.

PhD Program curriculum at MIT Sloan is organized under the following three academic areas: Behavior & Policy Sciences; Economics, Finance & Accounting; and Management Science. Our nine research groups correspond with one of the academic areas, as noted below.

MIT Sloan PhD Research Groups

Behavioral & policy sciences.

Economic Sociology

Institute for Work & Employment Research

Organization Studies

Technological Innovation, Entrepreneurship & Strategic Management

Economics, Finance & Accounting

Accounting  

Management Science

Information Technology

System Dynamics  

Those interested in a PhD in Operations Research should visit the Operations Research Center .  

PhD Program Structure

Additional information including coursework and thesis requirements.

MIT Sloan Predoctoral Opportunities

MIT Sloan is eager to provide a diverse group of talented students with early-career exposure to research techniques as well as support in considering research career paths.

Rising Scholars Conference

The fourth annual Rising Scholars Conference on October 25 and 26 gathers diverse PhD students from across the country to present their research.

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The goal of the MIT Sloan PhD Program's admissions process is to select a small number of people who are most likely to successfully complete our rigorous and demanding program and then thrive in academic research careers. The admission selection process is highly competitive; we aim for a class size of nineteen students, admitted from a pool of hundreds of applicants.

What We Seek

• Outstanding intellectual ability
• Excellent academic records
• Previous work in disciplines related to the intended area of concentration
• Strong commitment to a career in research

MIT Sloan PhD Program Admissions Requirements Common Questions

Dates and Deadlines

Admissions for 2024 is closed. The next opportunity to apply will be for 2025 admission. The 2025 application will open in September 2024. 

More information on program requirements and application components

Students in good academic standing in our program receive a funding package that includes tuition, medical insurance, and a fellowship stipend and/or TA/RA salary. We also provide a new laptop computer and a conference travel/research budget.

Funding Information

Throughout the year, we organize events that give you a chance to learn more about the program and determine if a PhD in Management is right for you.

PhD Program Events

May phd program overview.

During this webinar, you will hear from the PhD Program team and have the chance to ask questions about the application and admissions process.

June PhD Program Overview

July phd program overview, august phd program overview.

Complete PhD Admissions Event Calendar

Unlike formulaic approaches to training scholars, the PhD Program at MIT Sloan allows students to choose their own adventure and develop a unique scholarly identity. This can be daunting, but students are given a wide range of support along the way - most notably having access to world class faculty and coursework both at MIT and in the broader academic community around Boston.

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Profiles of our current students

MIT Sloan produces top-notch PhDs in management. Immersed in MIT Sloan's distinctive culture, upcoming graduates are poised to innovate in management research and education.

Academic Job Market

Doctoral candidates on the current academic market

Academic Placements

Graduates of the MIT Sloan PhD Program are researching and teaching at top schools around the world.

view recent placements 

MIT Sloan Experience

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The PhD Program is integral to the research of MIT Sloan's world-class faculty. With a reputation as risk-takers who are unafraid to embrace the unconventional, they are engaged in exciting disciplinary and interdisciplinary research that often includes PhD students as key team members.

Research centers across MIT Sloan and MIT provide a rich setting for collaboration and exploration. In addition to exposure to the faculty, PhD students also learn from one another in a creative, supportive research community.

Throughout MIT Sloan's history, our professors have devised theories and fields of study that have had a profound impact on management theory and practice.

From Douglas McGregor's Theory X/Theory Y distinction to Nobel-recognized breakthroughs in finance by Franco Modigliani and in option pricing by Robert Merton and Myron Scholes, MIT Sloan's faculty have been unmatched innovators.

This legacy of innovative thinking and dedication to research impacts every faculty member and filters down to the students who work beside them.

Faculty Links

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Student Research

“MIT Sloan PhD training is a transformative experience. The heart of the process is the student’s transition from being a consumer of knowledge to being a producer of knowledge. This involves learning to ask precise, tractable questions and addressing them with creativity and rigor. Hard work is required, but the reward is the incomparable exhilaration one feels from having solved a puzzle that had bedeviled the sharpest minds in the world!” -Ezra Zuckerman Sivan Alvin J. Siteman (1948) Professor of Entrepreneurship

Sample Dissertation Abstracts - These sample Dissertation Abstracts provide examples of the work that our students have chosen to study while in the MIT Sloan PhD Program.

We believe that our doctoral program is the heart of MIT Sloan's research community and that it develops some of the best management researchers in the world. At our annual Doctoral Research Forum, we celebrate the great research that our doctoral students do, and the research community that supports that development process.

The videos of their presentations below showcase the work of our students and will give you insight into the topics they choose to research in the program.

How Should We Measure the Digital Economy?

2020 PhD Doctoral Research Forum Winner - Avinash Collis

Watch more MIT Sloan PhD Program  Doctoral Forum Videos

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Engineering and Applied Science PhD

The Engineering and Applied Science Doctor of Philosophy program is an innovative multidisciplinary program designed to model modern research. Students choose a primary concentration from a host department within the College of Engineering, Design and Computing. The primary concentration is complemented by a secondary concentration in engineering or from any CU Denver school/college.

Host departments

Civil Engineering Computer Science and Engineering Electrical Engineering Mechanical Engineering

Degree requirements

The coursework in the primary and secondary areas must consist of ten courses—students must take at least five courses in his/her primary area of concentration and at least three courses in a secondary area of concentration. Other courses may be recommended by the student’s advisor.

Research spanning two or more of the five college departments is strongly encouraged and is a major strength of the program.

Coursework : 30 credit hours Research/dissertation : 30 credit hours Total : 60 credit hours

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Postgraduate Research (PhD)

The Dyson School of Design Engineering at Imperial College draws together teaching and research in the field, building on decades of design engineering successes across Imperial College and through its collaboration with the Royal College of Art.

Our academics and researchers have strong links with industrial, government and charity sectors with expertise and interests ranging from the design of complex systems to that of platforms, artefacts, consumer products and experiences. Imperial is a great place to work, being in the heart of London, surrounded by commercial organisations, innovation hubs and industry, museums, concert halls, places to eat and drink: an exciting meeting place for people from around the world. 

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Applying for a phd in design engineering.

More information and advice on submitting your application to study a PhD in Design Engineering

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Information for Current PhD Students

Essential information and resources you'll need as a PhD student in Design Engineering

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Information for new starters.

Essential information to help get you started in the department and your PhD

Funding Opportunities

Click here to see currently open PhD funding opportunities in both the School and the College

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PhD in Engineering

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The University of Cambridge Department of Engineering is one of the leading centres of engineering in the world, renowned for both its teaching and its research. Since its foundation in 1875, it has grown to become the largest department in the University, and the largest integrated engineering department in the UK, with approximately 150 faculty, 260 contract research staff and research fellows, 900 postgraduate students, and 1,200 undergraduates.

By the end of the PhD, students are expected to have produced original work making a significant contribution to knowledge in the field of engineering. At the same time, the Department expects that students will leave with the wider skills necessary to be successful in either an academic or a non-academic career.

The Department of Engineering offers PhD studies in a wide variety of subjects.  The Department is broadly divided into six Research Divisions, the strategic aims of which are broadly described below:

Energy, Fluid Mechanics and Turbomachinery

Building on research in fluid mechanics and thermodynamics to develop a systems view of energy generation and utilisation, particularly in the ground and air transport, to mitigate environmental impact. This Division's research focus includes acoustics, aerodynamics, combustion, energy use and generation, fluid mechanics and turbomachinery.

Electrical Engineering

Pursuing fundamental electrical, electronic and photonic research at the material, device and system levels with a focus on creating integrated solutions in the fields of nanotechnology, sensing, energy generation, energy conversion, displays and communications. The research in this division covers all aspects of electrical engineering from the nano-scale to heavy-duty power applications.

Mechanics, Materials and Design

Extending fundamental and applied research in mechanics, materials, bio-mechanics and design, exploiting cross-disciplinary partnerships across the University; and building on existing strengths to develop excellence in bioengineering and healthcare systems research.

Civil Engineering

Advancing the mechanics of civil and structural engineering systems within the broader context of the design, construction and operation of sustainable infrastructure and the stewardship of Earth's resources and environment.

Manufacturing and Management

Developing a new understanding of manufacturing technology, operations, strategy and policy, in close partnership with industry, in order to improve industrial performance.

Information Engineering

Developing fundamental theory and applications relating to the generation, distribution, analysis and use of information in engineering and biological systems.

It is not necessary to have a Master's degree to gain entry to the PhD; applicants can apply on the basis of their undergraduate degree (subject to international students meeting the minimum criteria for postgraduate entry to the University). Students applying with a taught Master's degree from Cambridge are expected to have achieved a mark of at least 70% overall on their programme.

The Postgraduate Virtual Open Day usually takes place at the end of October. It’s a great opportunity to ask questions to admissions staff and academics, explore the Colleges virtually, and to find out more about courses, the application process and funding opportunities. Visit the  Postgraduate Open Day  page for more details.

See further the  Postgraduate Admissions Events  pages for other events relating to Postgraduate study, including study fairs, visits and international events.

Key Information

3-4 years full-time, 4-7 years part-time, study mode : research, doctor of philosophy, department of engineering, course - related enquiries, application - related enquiries, course on department website, dates and deadlines:, lent 2024 (closed).

Some courses can close early. See the Deadlines page for guidance on when to apply.

Michaelmas 2024

Funding deadlines.

These deadlines apply to applications for courses starting in Michaelmas 2024, Lent 2025 and Easter 2025.

Similar Courses

• Engineering MPhil
• Construction Engineering MSt
• Nuclear Energy MPhil
• Connected Electronic and Photonic Systems MRes
• Future Infrastructure and Built Environment (part time) PhD

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PhD in Engineering Education Systems and Design

Ph.D. in Industrial Engineering

With the PhD in Industrial Engineering, gain a solid understanding of the theoretical bases for the latest tools and techniques of systems analysis and design, an extensive experience in applying these analyses and design tools and techniques, and research experience in the development of new tools or applications of existing techniques to design or analyze problems.

Ph.D. in Mechanical and Aerospace Engineering

With the PhD in Mechanical and Aerospace Engineering, prepare for advanced roles in industry or for a rewarding career in academia and research.

Ph.D. in Computer Science

With the PhD in Computer Science, prepare for advanced roles in industry or a rewarding career in academia and research.

Ph.D. in Electrical and Computer Engineering

With the PhD in Electrical and Computer Engineering, prepare for advanced roles in industry or a rewarding career in academia and research.

Ph.D. in Biological Engineering

Develop highly specialized skills in a subdivision of bioengineering and prepare for a rewarding career in academia and research.

Ph.D. in Chemical Engineering

Earn a PhD in Chemical Engineering and prepare for a career in academia and research, or for high-paying leadership roles in industry.

Ph.D. in Civil Engineering

Graduate programs offered in Engineering prepare students for leadership positions in academia, research and advanced practice engineering careers. Major program areas include structural mechanics, structural engineering and materials, geotechnical and geoenvironmental engineering, environmental engineering, hydrology and water resources engineering and transportation engineering.

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Top 10 Best PhD in Engineering Programs [2024]

You could secure a relatively successful career with a bachelor’s or master’s degree in engineering, so why would you need a PhD in engineering? The prevalence of engineering doctorate graduates  has steadily increased in the last 20 years by 6%. Maybe it has something to do with the fact that it’s one of the highest-paid PhD programs in 2024 !

A doctorate degree in engineering will equip you with advanced skills and knowledge, qualifying you for some of the highest positions in the sector, including unique research positions and esteemed professor roles.

With a doctorate of engineering, you’ll belong to a select group of professionals and enjoy a higher average salary than other engineers. Ready to take your engineering career to the next level? Check out our roundup of the best PhD engineering programs, along with career ideas and salary potential.

Table of Contents

Best PhD in Engineering Programs

Here’s a quick list of the best PhD in engineering programs:

• Washington University in St. Louis – PhD in Biomedical Engineering
• Duke University – Ph.D. – Civil & Environmental Engineering
• George Washington University – Doctor of Engineering in Engineering Management
• University of Missouri – Ph.D. in Biological Engineering
• University of Georgia – Ph.D. Engineering – Electrical and Computer Engineering
• Northeastern University – Ph.D., Mechanical Engineering
• Lehigh University – Ph.D. in Computer Science and Engineering
• University of Wisconsin – Chemical Engineering, Ph.D.
• Clemson University – Ph.D. in Mechanical Engineering
• Georgia Institute of Technology – Doctor of Philosophy in City and Regional Planning

Washington University in St. Louis, McKelvey School of Engineering

PhD in Biomedical Engineering

Named after George Washington, Washington University is a prestigious private research university with students from all 50 states as well as 120 countries. It has two campuses, one each in St. Louis and Clayton, Missouri.

If you have an undergraduate degree in a STEM discipline, you can apply for the university’s PhD in Biomedical Engineering program. As part of this fully-funded program, you’ll conduct research in one of the seven interdisciplinary frontier areas in biomedical engineering.

• Courses : Problem-based learning in biomedical sciences, mathematics of image science, and bioelectric phenomena.
• Credits : 72 (Post-bachelor’s)
• Duration : 5 years
• Tuition : $57,750 per year
• Financial aid : Fellowships
• Acceptance rate:  16%
• Location : St. Louis, MO

Duke University, Pratt School of Engineering

Ph.D. – Civil & Environmental Engineering

Duke University is a world-renowned private research university spread across a number of campuses that offers a diverse learning environment. This PhD program offers cross-disciplinary research opportunities, with the choice of one of five different research tracks available:

• Hydrology and Fluid Dynamics
• Environmental Health Engineering
• Computational Mechanics and Scientific Computing
• Engineering Environmental Geomechanics and Geophysics
• Systems, Risk, and Decision

Students are also eligible for full funding if they meet all requirements.

• Courses : Depends on the track, but some examples include chemical principles, advanced fluid mechanics, uncertainty qualification, game theory, and environmental microbiology
• Credits : 30
• Financial aid : Full funding, fellowships, awards
• Acceptance rate : 7.7%
• Location : Durham, North Carolina

The George Washington University

Doctor of Engineering in Engineering Management

George Washington University offers a doctoral program in Engineering Management with five different focus areas. Focus areas include crisis, emergency & risk management, engineering & technology management, and knowledge & information management. An online engineering PhD option is also available.

• Courses : Data analysis for engineers & scientists, the Praxis Proposal, and Praxis research.
• Credits:  45
• Tuition:  Refer to the tuition page
• Financial aid : Scholarships, federal work-study, loans
• Acceptance rate : 43%
• Location:  Washington, DC

The University of Missouri, College of Engineering

Ph.D. in Biological Engineering

The University of Missouri is a world-renowned public university offering more than 300 programs to students from all 50 states as well as 100 countries. Its PhD in Biological Engineering allows you to conduct research in interdisciplinary fields that combine subjects from both biological sciences and engineering. You’ll need to pass a qualifying examination after the first 18 months to continue in the program.

• Courses : Numerical methods in engineering research, seminar in biological engineering, and research in biological engineering.
• Semester hours : 72
• Tuition : $229.80
• Financial aid : Loans, scholarships fellowships, and assistantships
• Acceptance rate:  81.8%
• Location : Columbia, MO

The University of Georgia, College of Engineering

Ph.D. Engineering – Electrical and Computer Engineering

The University of Georgia is a public land grant research university in Athens, Georgia. Its PhD program in engineering allows for in-depth research into electrical and computer engineering technologies and investigates related advanced applications. You can apply to the program with only a bachelor’s degree, but you will have to complete additional credits.

• Tracks : Robotics & automation, electronics & photonics, and intelligent & cyber-physical systems
• Courses : Wireless sensor networks, advanced microcontrollers, and engineering informatics.
• Credits : 43 (for master’s degree holders), 73 (for bachelor’s degree holders)
• Tuition :  $8,704 per year
• Financial aid : Research assistantship, grants, scholarships, loans, federal work-study, veteran benefits
• Acceptance rate:  48.4%
• Location:  Athens, GA

Northeastern University, Department of Mechanical & Industrial Engineering

Ph.D., Mechanical Engineering

Northeastern University is a private research university in Boston. Its PhD program in Mechanical Engineering offers two modes of entry: direct entry for students with a bachelor’s degree and advanced entry for those with a master’s degree. You can also combine the program with the Gordon Engineering Leadership certificate.

• Courses : Materials science engineering, dynamic systems and control, and finite element method (FEM).
• Credit hours : 40 minimum (direct entry), 20 minimum (advanced entry)
• Tuition : $1,689 per credit hour
• Financial aid : Scholarships, fellowships, assistantships, awards, and loans
• Acceptance rate:  20.5%
• Location:  Boston, Massachusetts

Lehigh University, P.C. Rossin College of Engineering & Applied Science

Ph.D. in Computer Science and Engineering

Located in Pennsylvania’s Lehigh Valley, Lehigh University is a world-renowned private research college with a special focus on interdisciplinary research, with a collaborative approach. This PhD program allows you to explore state-of-the-art computer science fields such as artificial intelligence, robotics, and social computing. You’ll also have access to interdisciplinary studies through other departments within the institution, as well as other universities and external laboratories.

• Courses : Advanced programming techniques, Artificial Intelligence theory & practice, and design & analysis of algorithms.
• Duration : 4-6 years
• Tuition : $1,500 per credit hour
• Financial aid : Research assistantships, teaching assistantships, fellowships
• Acceptance rate : 49.5%
• Location : Bethlehem, PA

University of Wisconsin – Madison, Department of Chemical and Biological Engineering

Chemical Engineering, Ph.D.

The University of Wisconsin is a public land-grant research university and the flagship university of the University of Wisconsin System. Its PhD program in Chemical Engineering has been among the most prestigious such programs for more than a century. The school conducts research in a wide range of subjects, such as energy-related science and technology, complex fluids, polymers synthesis and processing, and atomic-scale design of surface reactivity.

• Courses : Advanced chemical engineering thermodynamics, and biological engineering: molecules, cells & systems.
• Credits : 51 minimum
• Tuition : $773 per credit
• Financial aid : Loans, scholarships, grants, federal work-study, veteran benefits
• Acceptance rate : 57.2%
• Location:  Madison, WI

Clemson University, Department of Mechanical Engineering

Ph.D. in Mechanical Engineering

Clemson University is a private land grant university with a range of research projects in agriculture, energy, and engineering, among other fields. This PhD program includes a thesis and a non-thesis option. You’ll have the opportunity to conduct research at various renowned institutes, including the Dominion Energy Innovation Center (EIC) of Clemson University. You can transfer a maximum of 12 credits from your graduate coursework.

• Courses : Foundations of fluid mechanics, intermediate dynamics, modern control engineering, and design methodology.
• Credit hours : 24 (with thesis), 33 (non-thesis)
• Tuition : Refer tuition page
• Financial aid : Grants, scholarships, loans, student employment, etc.
• Acceptance rate : 61.9%
• Location : North Charleston, SC

Georgia Institute of Technology, School of City & Regional Planning

Doctor of Philosophy in City and Regional Planning

Georgia Institute of Technology, or Georgia Tech, is a well-known university with a core focus on technology. Its PhD in city and regional planning is a specialized doctorate of engineering program that allows you to work with other research centers, schools, and programs. Core subjects include the construction of healthy cities, disaster planning, urban analytics, and climate change.

• Courses : Advanced planning theory, quantitative research design & methods, and advanced urban and regional development theory.
• Credits : 46
• Duration : 2 years minimum
• Tuition : $586 per credit
• Financial aid : Research assistantships, scholarships, loans, and fellowships
• Acceptance rate : 21.3%
• Location : Atlanta, GA

Why Get a Degree in Engineering?

An engineering degree teaches you to look at the most modern, advanced, innovative, and constructive parts of the world. With an advanced degree in the field, you’ll gain problem-solving, analytical and critical thinking, development, and creative skills.

Furthermore, a PhD in Engineering will qualify you to apply for some of the most lucrative jobs in the industry. You will have several capabilities enabling you to take up almost any kind of project.

Top Careers for PhD in Engineering Graduates

Here are some of the jobs you’re most likely to score with an engineering PhD, along with the annual median salary for each:

• Engineering Manager ( $118,900 )
• Research Engineer ( $83,112 )
• Engineering Professor ( $89,213 )
• Design Engineer ( $69,821 )
• Aerospace Engineer ( $86,034 )
• Chemical Engineer ( $76,689 )
• Test/QA Engineer for Computer Software ( $71,633 )

Scholarships for Engineering PhD Programs

Many universities offer a range of scholarships, fellowships, and awards to deserving doctorate candidates.

Here are some of the scholarships offered by the country’s most prestigious universities:

• Sloan Scholarships:  You’ll need US citizenship and admission to one of Duke University’s PhD programs to be eligible. Scholarship recipients receive $40,000 over five years.
• University of Missouri 5-Year Fellowship Programs:  The University of Missouri offers seven fellowship programs for eligible students admitted to the university’s doctoral programs. The program includes a tuition waiver, five years’ support, and an insurance subsidy.
• Dean’s International Award :  Washington University in St. Louis awards this scholarship to candidates applying to their PhD engineering programs and are currently pursuing an undergraduate or master’s program.
• Northeastern University Dissertation Completion Fellowship:  Eligible doctoral students at Northeastern University may be awarded a stipend for their final semester.
• Regent’s Opportunity Scholarship : This is a renewable scholarship of $5,500 per year offered by the Georgia Institute of Technology for minority in-state students.

Related:  Top Online PhD Programs in 2024

PhD in Engineering FAQs

Is a phd useful in engineering.

A doctorate degree in engineering can attract a higher salary than a master’s alone. Additionally, a PhD in engineering opens more opportunities to do innovative projects and grow your career.

What is the Best PhD in Engineering?

There is no single best PhD engineering program. The best program for you depends on your preferred discipline, schedule, and goals. Once you decide your focus, look for reputable, accredited universities offering the best engineering PhD programs in your desired specialty.

What is the Highest Degree in Engineering?

A PhD is considered the highest degree in engineering. This qualification will help you secure roles at the highest levels of the industry.

How Long is a PhD in Engineering?

A typical PhD in engineering takes between  five and seven years  to complete. However, this can vary depending on the program, your own preferences, and requirements. For example, there are online engineering PhD programs and accelerated programs that you can complete more quickly.

What Percentage of Engineers have a PhD?

Not all engineers have a doctorate, but those who do are at an advantage. According to Forbes , the proportion of engineering doctorates among all PhD holders increased from 12.9% to 18.9% from 2000 to 2020. Additionally, over 11,000 engineering doctorates  were awarded in 2019.

Key Takeaways

Not many engineers pursue a doctorate after their master’s — but doing so will put you in a competitive position. You’ll be equipped with high-level research skills that will set you apart from your colleagues.

A PhD in engineering will give you an advanced level of knowledge that will propel your performance in your current role, prepare you for promotion and more leadership roles, and equip you to take on the most challenging assignments in the industry. On top of all that, you’ll be rewarded with a lucrative salary.

If you’re ready to put together your applications for the best engineering PhD programs, check out our guides to writing your academic resume  and how to ask a professor for a letter of recommendation.

You May Also Like:

• Top 20 Best PhD Programs in California [Online and On-Campus]
• Top 10 Best Online PhD Programs in Texas

Lisa Marlin

Lisa is a full-time writer specializing in career advice, further education, and personal development. She works from all over the world, and when not writing you'll find her hiking, practicing yoga, or enjoying a glass of Malbec.

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The DESIGN Graduate Experience

The Engineering Design (DESIGN) graduate program prepares the innovators of the future. We integrate the disciplines of engineering with design theory, business, psychology, and art through project-based learning. Through the graduate program, students develop the technical depth and breadth to solve problems related to products, systems, processes, and services. 

Become a Master Designer

We are real-life problem solvers, focusing our curriculum on collaborative, client-driven project-based learning. We are creative thinkers and innovators, designing solutions to society's most complex dilemmas. 

We help you master DESIGN. 

Master of engineering in engineering design.

• Intensive one-year, 32-credit program
• Completion of an engineering internship or a scholarly paper
• Ideal for working engineers who wish to dive deeper into design

Master of Science in Engineering Design

• Comprehensive two-year, 32-credit program
• Completion of a thesis
• Ideal for engineers wishing to pursue a traditional two-year, research-based master's degree

Both degrees provide ample opportunities for students to sharpen their holistic design skills while gaining substantial practical experience in a studio environment. Both offer a chance to explore engineering challenges through multidimensional context-specific lenses, from beginning to end—helping students become master designers. 

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The School of Engineering Design and Innovation delivers effective engineering education and unrivaled research opportunities through active, collaborative, project-based, and professionally oriented classroom experiences. The school offers a variety of programs that partner faculty, students, and industry in the study of real-life engineering problems. Our programs teach students to solve real-life problems with innovative solutions. 

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Design (PHDESIG)

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Phd - industrial design engineering.

PhD programme (doctoral degree)

Studier PHD-faktaboks

• PhD Full time, 3 years
• Campus Trondheim and Gjøvik
• Admission Application and admission
• Application deadlines Ongoing admissions

The PhD program in design is research training for those who have a master's degree.

More and more industries need the specialization that the PhD education provides: a good basis for leading work in business, administration, education and research.

About the programme

The PhD program is standardized to 180 ECTS credits, 3 years of full-time study.

It is academically linked to the Department of Design, where the main areas are product design, interaction design, graphic and information design, sustainable design, design theory and health-related design.

Read more about the programme

Programme structure

The programme consists of a coursework part of a minimum of 30 ECTS credits and a doctoral thesis. The thesis may consist of a monograph or a collection of several smaller works.

The coursework and the work on the thesis are carried out in parallel. It is recommended, however, that the coursework be completed early in the course of study. All the coursework must have been completed and approved before you submit the thesis.

The coursework can be taken at other faculties at NTNU or at other higher education institutions that provide doctoral education. You must have taken the final exam or received another form of assessment for all subjects included in the coursework.

You decide on the courses in agreement with your supervisor. The courses are adapted to the subject matter of your thesis.

Read more about the programme structure

Career opportunities

Working life increasingly appreciates the specialization that the PhD program provides, and surveys show that people with a doctorate quickly achieve leading positions.

Read more about career opportunities

How to apply and admission

In order for you to be admitted to the doctoral program, you must have a five-year master's degree or equivalent education with an average grade equivalent to B or better in the last two years.

The master's degree must normally be within a subject area that falls under the PhD program in design. If you have a different professional background, you can be admitted after an overall assessment of the project, theme and project description.

Read more about how to apply and admission

Please contact us should you have any questions about the program.

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Courses for Engineering Education PhD

Course navigation, engineering education (ened) courses, courses from the school of education.

• Courses from across the University  
• Flexible courses

Courses highly recommended by the School of Education for Engineering Education PhD Students: 

Other courses available through the school of education: .

School of Education Course Catalog

• Advanced Social Foundations of Education (EDUC 5005)
• Race and Equity in Higher Education (EDUC 5010)
• Assessment in Mathematics and Science Education (EDUC 5706)
• Basic Statistical Methods (EDUC 5716)
• Introduction to Disciplined Inquiry (EDUC 5726)
• Student Affairs in Higher Education (EDUC 6110)
• Ethics in Education (EDUC 6230)
• Psychological Foundations of Education (EDUC 6318)
• Anthropology of Education (EDUC 6325)
• College Student Development and Counseling Theories (EDUC 6405)
• Issues and Methods in Cognitive Science (EDUC 6504)
• Leadership in Higher Education (EDUC 6705)
• EDUC 7316 has a pre-requisite course of Basic Statistical Methods (EDUC 5716)
• Quasi-Experimental design in causal inference in social sciences (EDUC 7326)
• EDUC 7336 has two pre-requisite courses: Introduction to Disciplined Inquiry (EDUC 5726) and Intermediate Statistical Methods (EDUC 7316) 
• Educational Evaluation (EDUC 7386)
• Advanced Qualitative Data Analysis (EDUC 8730)
• Mixed Methods in Educational Research (EDUC 8735)

Courses that may be available to Engineering Education PhD Students, but are generally restricted to PhD students in the school of Education: 

• Critical inquiry into becoming a teacher educator (EDUC 7115)
• Ways of Knowing in Educational Research (EDUC 8210)

Courses from across the university

Flexible courses for engineering education phd .

The Engineering Education PhD program is very open to technical and education courses the PhD candidate believe are necessary for their academic success. Some suggested courses are:

• Leading Oneself (EMEN 5050)
• Leading Others (EMEN 5052)
• Neuroscience of Leadership (EMEN 5054)
• Leading for Diversity, Equity and Inclusion in Engineering (EMEN 5055)
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Engineering Education

College of Engineering and Applied Science » Academics » Departments » Engineering & Computing Education » Majors & Programs » Ph.D in Engineering Education

Why study Engineering Education?

The University of Cincinnati’s graduate degree in Engineering Education will prepare students to design and execute a research agenda that advances the knowledge base in engineering education, while in parallel advancing their expertise within a technical engineering discipline of their choice. In addition, each student will specialize in one of three focus area options: higher education in engineering, engineering education in PreK-12 levels (formal and informal environments, for- or non-profit), or engineering industry and workforce development. A degree in engineering education can lead to a career in academia, industry, or government.

Engineering education research, as a discipline, builds on the theories, methods of inquiry, and ways of knowing that have been and continue to be developed in related disciplines - including anthropology, diversity equity and inclusion studies, economics, education, neuroscience, philosophy, political science, psychology, and sociology, along with education research in science, technology, and mathematics - through the lens of engineering. Students will be introduced to theories related to the teaching and learning of engineering, the applications of pedagogy and assessment, as well as develop advanced knowledge on research methods, including quantitative, qualitative and mixed methods of inquiry.

Admission Requirements

• GRE - Required of all international students; GRE is exempt for students that earned a degree from an ABET accredited university (or equivalent accreditation) in the USA with a GPA of 3.0+
• Transcript(s) and Degree Certificates (unofficial transcripts are used for admissions review, only admitted applicants submit official transcripts)
• GPA of at least 3.0 in a Bachelor’s or Graduate degree program in engineering, mathematics, or the physical sciences from a college or university regarded as standard by a regional or general accrediting agency
• Research Statement - (1-3 pages) should describe your research interests (see below), with specific reference to the research area(s), engineering education research methodology, and focus area. You may choose to build on or tie in prior research experience. This statement is used by the faculty as an example of your writing, to help gauge your potential to effectively engage in research at this degree level, and to help determine if the Engineering Education program is a good fit.
• Statement of Purpose - (1-2 pages) should include brief narratives about: a) your academic, professional, and previous research experiences (if not discussed in your research statement); b) your immediate and long-range aspirations; c) how the Engineering Education program will help you to meet your goals; and d) any additional information you feel strengthens your application (e.g., your perspective on the relationship between educational research and teaching/learning). This statement is used by the faculty as an example of your writing and to help determine if the Engineering Education program is a good fit.
• Curriculum Vita (resume) - should include your name(s), a phone number, e-mail address, and colleges attended with degrees and dates. Also include, if applicable, employment history, honors and awards, publications and presentations, and relevant professional experiences (e.g., research, teaching/tutoring, service). Your CV does not need to be structured with these sections and is not limited to these items.
• Two letters of recommendation.
• International students - English Proficiency Test: TOEFL (minimum 92) or IELTS (minimum 6.5)

Description of Engineering Education Research Areas:

• Engineering Epistemologies : research on what constitutes engineering now and into the future
• Engineering Learning Mechanisms : research on developing engineering learners’ knowledge and expertise
• Engineering Learning Systems : research on the instructional culture and knowledge required of engineering educators
• Engineering Diversity and Inclusiveness : research on how diverse human talents contribute to the social and global relevance of our profession
• Engineering Education Assessment and Research Methodologies : research on, and the development of, the quantitative, qualitative, and/or data scientific aspects of engineering education (i.e., how theories are studied, designed for, and assessed), including assessments, instruments, and protocols

Description of Engineering Education Research Methodologies:  

• Quantitative Research  emphasizes objective measurements and the statistical, mathematical, or numerical analysis of data.
• Qualitative Research  seeks to produce in-depth descriptions and interpretations of human behaviors and experiences based primarily on the words of selected individuals (e.g., through interviews) and/or through the interpretation of actions (e.g., observations) or artifacts (e.g., analysis of documents).
• Mixed Methods Research  is characterized by (among other features) drawing on the strengths of both quantitative and qualitative methods for generating possible solutions or holistic understandings of the problem that may not have been possible using either method by itself.

Description of Engineering Education Graduate Program Focus Areas:

• Higher Education in Engineering : Research will focus on higher education contexts (e.g., undergraduate students, graduate students, faculty).
• Engineering Education in PreK-12 : Research will focus on PreK-12 contexts (e.g., students, parents, teachers, administration; formal and informal environments, for- or non-profit). (Note: This focus area does not lead to teacher licensure.)
• Engineering Industry and Workforce Development : Research will focus on industry and workforce development contexts (e.g., practicing engineers; management; translating among technical content, management, leadership, and andragogy).

The Ph.D. ENED program will prepare graduates for careers: at universities (traditional technical disciplines and/or departments of engineering education); at community colleges; in PreK-12 schools; in for-profit and non-profit organizations (e.g., testing organizations, foundations, governmental agencies); in programmatic roles (e.g., assessment and accreditation coordinators, curriculum designers, policy makers, program officers); as corporate trainers and other workforce development positions; and as directors of teaching/learning centers, diversity programs, or outreach programs.

The Ph.D. ENED program at UC is differentiated from other similar programs in four ways: 

• The program has a strong emphasis on developing in-depth educational research skills (based on research methodology coursework requirements).
• The program requires students to advance their level of expertise within their technical engineering discipline.
• Thee program allows students to choose one of three focus areas depending on their background and goals: higher education in engineering, engineering education in PreK-12 levels (formal and informal environments, for- or non-profit), or engineering industry and workforce development (to the best of our knowledge, workforce development is not an explicit emphasis in any of the existing M.S. or Ph.D. programs at other institutions).
• The program leverages the strong foundation of experiential learning within the College of Engineering and Applied Science (CEAS) by requiring students to complete a reflective experiential activity.
• Guide: 20DOC-ENED-PHD

Application Deadlines

Early Admission

General Admission

Application deadlines and additional application information can be found at the  CEAS Office of Graduate Studies .

Contact Information

Find related programs in the following interest areas:.

• Engineering

Program Code: 20DOC-ENED-PHD

Master in Design Engineering

The Master in Design Engineering (MDE) program prepares the next generation of leaders to create transformative solutions that positively improve society. The integrated fields of design and engineering are uniquely positioned to address the world’s toughest challenges.

Our world faces increasingly complex, often unpredictable dilemmas of consequence to human lives and living environments, including rapid urbanization, climate change, and resource scarcity. These and other problems demand a deep and systems-level understanding of the underlying problem architecture, which in turn enables innovative, multi-faceted solutions that transcend disciplines and scales. The MDE program prepares innovators who operate both creatively and analytically, think strategically, and collaborate broadly. MDE graduates lead change and advance novel, real-world solutions.

The Master in Design Engineering is a collaborative degree program between the Harvard University Graduate School of Design and the Harvard John A. Paulson School of Engineering and Applied Sciences.

Learn more about MDE

To learn more about the curriculum, admissions criteria, resources, student life, and more, visit the Master in Design Engineering website .

2023 Outstanding Design Engineering Project Award: Rebecca Brand and Caroline Fong’s Jua: Cultivating Digital Knowledge Networks for Smallholder Farmers

by Rebecca Brand (MDE ’23) and…

Jock Herron , Faculty Advisor

Spring 2023

Smart Toilet Paper

by Anesta Iwan (MDE ’19) — Recipient of the Outstanding Design Engineering Project Award…

Martin Bechthold , Peter Stark and Mary Tolikas, Faculty Advisors

Spring 2019

Making a New City Image . . . or, An Eye for AI

by Brian Ho (MDE ’18) Making a New City Image explores the machine-mediated perception of urban…

Robert Pietrusko, Faculty Advisor

Spring 2018

Student Work

Pharma 2100

by Anesta Iwan (MDE ’19)) Is our country focused more on fixing our problems or…

Remesys: Reanimating Emotional System

by Saif Haobsh (MDE ’19), Erin McLean (MDE ’19) Aging in place requires distinct kinds…

Underutilized Strategies in the American Multifamily Sector: How Community, Branding, and Amenities Could Reshape the Residential Apartment Market

Kevin Michael Sievers (MDes ’17) This research investigates three current industry trends in the multifamily…

Spring 2017

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Human Factors/Ergonomics

Degree concentration for phd, industrial engineering.

Human factors and ergonomics (HFE) applies industrial engineering, physiology, psychology, and computer science to the design of working and living environments with explicit consideration of the physical and mental characteristics of users.

Faculty and students in HFE conduct research in areas such as human-automation interaction, mathematical modeling of human performance, inclusive design, occupational safety, workplace design, cognitive engineering, and biomechanics.

Our department has a 50-year history of quality education and research in HFE. UB's IE program is one of the few graduate programs offered within an engineering school to be accredited by the Human Factors and Ergonomics Society. We have an active student body, as evidenced by our award-winning student chapter of the Human Factors and Ergonomics Society. 

HFE research is funded by such agencies as the U.S. Department of Transportation, the National Science Foundation, the National Institute for Occupational Safety and Health, the National Institute on Disability, Independent Living, and Rehabilitation Research, the Agency for Healthcare Research and Quality and the National Institutes of Health, as well as national and local corporations.

Our graduating students take human factors positions in academic institutions, federal laboratories, and national corporations.

Required Core Courses

IE PhD students who concentrate in HFE complete at a minimum:

• IE 531 Research Methods
• IE 507 Design and Analysis of Experiments
• IE 532 Human Information Processing
• IE 536 Physiological Foundations of Human Factors
• One Elective Course:  Choose one 500 or 600 level Human Factors Course (e.g., IE 541, Human Factors in Safety; IE 535, Human Computer Interaction; any 600 level special topics course or other HF course)

Media arts and sciences PhD redesigns community through research in human-computer Interaction

Photo courtesy of Alejandra Rodriguez Vega

Editor’s note:  This story is part of a series of profiles of  notable spring 2024 graduates .

Alejandra Rodriguez Vega, who is receiving her PhD from the media arts and sciences program in the School of Arts, Media and Engineering, focuses on designing with communities based on collaborative design approaches and user-centered design.

Rodriguez Vega has contributed valuable research to the local arts and academic communities during her graduate (MS and PhD) studies. Projects like “The Dream Collective” utilize crowdsourcing as a way to collect data about the experience of the modern classroom and how it can be re-designed to enhance the learning experience. She has also worked with Citizen Science to help design Pollinator Gardens for the local Mirabella at ASU community.  

Rodriguez Vega credits Associate Professor Stacey K.,  in the School of Arts, Media and Engineering, and her as a source of inspiration for introducing her to the research area of human- computer interaction early in her graduate studies. Having the opportunity to help work behind the scenes for the 2019 Tangible Embedded and Embodied Interaction conference that took place at ASU’s Tempe campus inclined her to further pursue graduate studies with a PhD in media arts and sciences.

“I wanted to be a part of this and continue collaborating with these brilliant minds who are not only very technically gifted but also incredibly creative,” she said.

While Rodriguez Vega attributes acceptance into the PhD program to hard work and luck, her dedication to contributing her valuable perspective to the research fields stood out to faculty.

During her studies in the MS media arts and sciences program, she collaborated with the SANDS (Social and Digital Systems Group) research lab. This led to her finishing her MS with a publication that was published at the 2019  Designing Interactive Systems conference. This experience prepared her for the world of dissertation and defense that is typical within the realms of PhD studies.

“The paper focused on a workshop that we did with the community scientists, revolving around interaction with drones,” Rodriguez Vega said. “That was really the starting point of doing hands-on research, seeing the publication process, as well as presenting my research to my fellow peers, faculty and researchers from all over the world. And I was lucky enough that I had that experience during my first summer of my masters, so preparing to go into my PhD, I had a pretty good idea of at least how the first few years were going to be.”

Rodriguez Vega entered graduate studies with a background in communication and interest in the interactions that take place between humans and computer systems. She was able to explore these interactions in various ways, from co-developing an online creativity tool, “The Dream Collective,” and creating a friendly user interface, to holding in-person workshops with participants where users’ needs and aspirations for future technologies were brought to life through low-fidelity prototypes. 

“I specifically decided to focus on what is called ‘collaborative design.’ This is an area of research that talks with all stakeholders and gives them the opportunity to iterate on any part of the design process and voice their concerns, desires and likes or dislikes,” she said. “The focus is really trying to understand user needs and expectations of designs and then working with engineers, designers and researchers to see how these changes can be brought to life. My research specifically focuses on integrating speculative methodologies into collaborative design so that participants are not limited by technological knowledge or feasibility when ideating and voicing their concerns, as well as, through online collaborative ideation tools, being able to collaborate with stakeholders at a larger scale.”

Most recently, Rodriguez Vega has worked on a project focused on collaborative design with the Center for the Future , an ASU-Starbucks partnership. 

Rodriguez Vega has received multiple scholarships and awards through her studies, such as the Graduate Completion Fellowship (2023–24), Graduate College Travel Award (2022), Creative Constellation Grant (2021), University Graduate Fellowship (2020), Outstanding Graduating Student (2019) and Katherine K. Herberger Scholarship (2018).

Question: What’s something you learned while at ASU — in the classroom or otherwise — that surprised you or changed your perspective?

Answer: My original background was in the humanities, so I was really scared of all these coding classes and thought they were going to be math heavy. I quickly learned otherwise, and I especially thank the faculty at AME, as they help you understand the logic behind coding and how it can be applied to art and creative outlets. I don’t think that that was something that I have ever encountered before or even thought possible, so that was very interesting to learn and tackle.

Q: Why did you choose ASU?

A: It was actually the weather. I don’t think a lot of people would say that, but I do like the heat for one thing. On a more serious note, the biggest thing was I didn’t find any other universities or programs that had a similar program like media arts and sciences — where it’s not completely engineering and it’s not completely art — it’s a mixture of both as well as design. This was extremely attractive to me, because I don’t have a background in engineering and didn't have the pressure of going into it thinking ‘Oh no, I need to know how to code!’ This really helped me get in the door having a bit of an understanding in engineering, design and art. Now, with my experience through research, I can communicate with engineers and programmers along with designers to produce meaningful and user-friendly interactions.

Q: Which professor taught you the most important lesson while at ASU?

A: My PhD chair, Stacey K. Her extensive background in human computer interaction has been extremely eye-opening. It has also made me realize my passion so that was extremely helpful while doing my PhD. She has taught me to be a better writer and a better researcher and how to approach people, handle workshops, and how to analyze data. She has been essential throughout my PhD journey.

I also have to mention Professor Kimberlee Swisher, I was her teacher’s assistant for quite a bit and although I never took a class with her since she teaches undergrad, she really inspired me to be a better educator and mentor and understand how to relate to people better when tackling problems. Really, all the faculty and staff within AME deserve recognition as they are great in helping you find a solution. If you have a crazy idea or a random question, even if it’s really out there, they’ll ask for more details and help find a solution. This would not have been doable without such a supportive department.

Q: What’s the best piece of advice you’d give to those still in school?

A: My best advice would be to ask a lot of questions. A lot of times you hear faculty say go to office hours or if you have any questions, come up and ask me, I’ll be here and not a lot of people take that opportunity. What I’ve learned is that the amount of knowledge that everyone has is beyond what you expect and if you really want to make the most out of your time here, whether it’s undergraduate or graduate studies,  start a conversation with faculty and staff, because they really do want to help you. Not only can this help you make connections, but it also helps you figure out what you want to do for a career.

Q: What was your favorite spot on campus, whether for studying, meeting friends or just thinking about life? 

A: It was probably the graduate student lounge in Matthews Center (on the Tempe campus). I was able to meet my fellow grad students, and just being able to talk with them and hang out really helped with making friends but also understanding their approach to their own research and writing. I think one of the things that really separates graduate studies from undergraduate studies is that everyone is doing their own research, writing their own papers, so this can become lonely sometimes. Having the Matthews Center created a space where I could talk with other students and understand the struggles they're going through and how they tackled challenging times.

Q: What are your plans after graduation?

A: I am hoping to go into user experience research in industry. User experience research allows us to collaborate, ideate and design alongside stakeholders such as users, designers, engineers and programmers to see what works, what doesn’t work, and what can be improved in a current technology, service or experience and even speculate on the future. 

Q: If someone gave you $40 million to solve one problem on our planet, what would you tackle?

A: I don’t think $40 million would be enough to tackle a specific problem on our planet. However, I do think a way to start tackling a lot of problems would be by educating people, so one of the things I think we could heavily invest in would be in education. I think now more than ever, teachers and middle school teachers lack funding and support. This money could be used to give teachers and students a better starting point to further educate them and have them be aware of problems and ways to solve the problems. Not just getting information out about things like global warming but actually giving them the time and resources to solve the problems through collaborative work. Education can be a great starting point or a foundation to actually solve problems.

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National Center for Science and Engineering Statistics

• All previous cycle years

The NSCG is a biennial survey that provides data on the characteristics of the nation's college graduates, with a focus on those in the science and engineering workforce.

Survey Info

• tag for use when URL is provided --> Methodology
• tag for use when URL is provided --> Data
• tag for use when URL is provided --> Analysis

The NSCG is a unique source for examining the relationship of degree field and occupation in addition to other characteristics of college-educated individuals, including work activities, salary, and demographic information.

Areas of Interest

• Science and Engineering Workforce
• STEM Education

Survey Administration

This survey was conducted by the Census Bureau in partnership with the National Center for Science and Engineering Statistics within the National Science Foundation.

Survey Details

• Survey Description (PDF 123 KB)
• Data Tables (PDF 2.1 MB)

Featured Survey Analysis

Effects of the COVID-19 Pandemic on Employment, Earnings, and Professional Engagement: New Insights from the 2021 National Survey of College Graduates

NSCG Overview

Data highlights, the share of u.s. college graduates employed full time trended downward between 2015 and 2021..

Unemployment increased across all levels of education between 2019 and 2021.

Methodology

Survey description, survey overview (2021 survey cycle).

The National Survey of College Graduates (NSCG)—sponsored by the National Center for Science and Engineering Statistics (NCSES) within the National Science Foundation (NSF)—provides data on the characteristics of the nation’s college graduates, with a focus on those in the science and engineering workforce. It samples individuals who are living in the United States during the survey reference week, have at least a bachelor’s degree, and are younger than 76. By surveying college graduates in all academic disciplines, the NSCG provides data useful in understanding the relationship between college education and career opportunities, as well as the relationship between degree field and occupation.

Data collection authority

The information collected in the NSCG is solicited under the authority of the NSF Act of 1950, as amended, and the America COMPETES Reauthorization Act of 2010. The Census Bureau collects the NSCG data under the authority of Title 13, Section 8 of the United States Code. The Office of Management and Budget control number is 3145-0141.

Major changes to recent survey cycle

The 2021 NSCG data collection instrument included new questions to gauge the effects of the coronavirus pandemic on employment, specifically on labor force status, number of hours worked per week, salary, benefits, telecommuting options, and total earned income.

Key Survey Information

Initial survey year, reference period.

The week of 1 February 2021.

Response unit

Individuals with at least a bachelor’s degree.

Sample or census

Population size.

Approximately 68.6 million individuals.

Sample size

Approximately 164,000 individuals.

Key variables

Key variables of interest are listed below.

• Demographics (e.g., age, race, sex, ethnicity, and citizenship)
• Educational history
• Employment status
• Field of degree

Survey Design

Target population.

The NSCG target population includes individuals who meet the following criteria:

• Earned a bachelor’s degree or higher prior to 1 January 2020,
• Are not institutionalized and reside in the United States or Puerto Rico as of 1 February 2021, and
• Are younger than 76 years as of 1 February 2021.

Sampling frame

The 2021 NSCG retains the four-panel rotating panel design that began with the 2010 NSCG. As part of this design, every new panel receives a baseline survey interview and three biennial follow-up interviews before rotating out of the survey.

The 2021 NSCG includes approximately 164,000 sample cases drawn from the following:

• Returning sample from the 2019 NSCG who were originally selected from the 2013 American Community Survey (ACS)
• Returning sample from the 2019 NSCG who were originally selected from the 2015 ACS
• Returning sample from the 2019 NSCG who were originally selected from the 2017 ACS
• New sample selected from the 2019 ACS

Approximately 90,000 cases were selected from the returning sample members for one of the three biennial follow-up interviews that are part of the rotating panel design. For the baseline survey interview, about 74,000 new sample cases were selected from the 2019 ACS.

Sample design

The NSCG uses a stratified sampling design to select its sample from the eligible sampling frame. Within the sampling strata, the NSCG uses probability proportional to size or systematic random sampling techniques to select the NSCG sample. The sampling strata were defined by the cross-classification of the following four variables:

• Young graduate oversample group eligibility indicator (2 levels)
• Demographic group (9 levels)
• Highest degree type (3 levels)
• Detailed occupation group (25 levels)

As has been the case since the 2013 NSCG, the 2021 NSCG includes an oversample of young graduates to improve the precision of estimates for this important population.

Data Collection and Processing

Data collection.

The NSCG uses a trimodal data collection approach: Web survey, mail survey, and computer-assisted telephone interview (CATI). The 2021 NSCG data collection effort lasted approximately 7 months.

Data processing

The data collected in the NSCG are subject to both editing and imputation procedures. The NSCG uses both logical imputation and statistical (hot deck) imputation as part of the data processing effort.

Estimation techniques

Because the NSCG is based on a complex sampling design and subject to nonresponse bias, sampling weights were created for each respondent to support unbiased population estimates. The final analysis weights account for several factors, including the following:

• Adjustments to account for undercoverage of recent immigrants and undercoverage of recent degree-earners
• Adjustment for incorrect names or incomplete address information on the sampling frame
• Differential sampling rates
• Adjustments to account for non-locatability and unit nonresponse
• Adjustments to align the sample distribution with population controls
• Trimming of extreme weights
• Overlap procedures to convert weights that reflect the population of each individual frame (2013 ACS, 2015 ACS, 2017 ACS, and 2019 ACS) into a final sample weight that reflects the 2021 NSCG target population.

The final sample weights enable data users to derive survey-based estimates of the NSCG target population.

Survey Quality Measures

Sampling error.

Estimates of sampling errors associated with this survey were calculated using the successive difference replication method. Please contact the NSCG Survey Manager to obtain the replicate weights.

Coverage error

Any missed housing units or missed individuals within sample households in the ACS would create undercoverage in the NSCG. Additional undercoverage errors may exist because of self-reporting errors in the NSCG sampling frame that led to incorrect classification of individuals as not having a bachelor’s degree or higher when in fact they held such a degree.

Nonresponse error

The weighted response rate for the 2021 NSCG was 65%. Analyses of NSCG nonresponse trends were used to develop nonresponse weighting adjustments to minimize the potential for nonresponse bias in the NSCG estimates. A hot deck imputation method was used to compensate for item nonresponse.

Measurement error

The NSCG is subject to reporting errors from differences in interpretation of questions and by modality (Web, mail, or CATI). To reduce measurement errors, the NSCG questionnaire items were pretested in focus groups and cognitive interviews.

Data Availability and Comparability

Data availability.

Data from 1993 to the present are available at the NSCG Web page .

Data comparability

Year-to-year comparisons can be made among the 1993 to 2021 NSCG survey cycles because many of the core questions remained the same. Small but notable differences exist across some survey years, such as the collection of occupation and education data based on more recent taxonomies. Also, because of the use of different reference months in some survey cycles, seasonal differences may occur when making comparisons across years.

There is overlap in the cases included in the 2010 NSCG through the 2017 NSCG, in the 2013 NSCG through the 2019 NSCG, and in the 2015 NSCG through the 2021 NSCG. This sample overlap consists of cases that originated in the 2013 ACS, 2015 ACS, 2017 ACS, or 2019 ACS. The overlap among cases allows for the ability to conduct longitudinal analysis of this subset of the NSCG sample. To reduce the risk of disclosure, longitudinal analyses can be conducted only within a restricted environment. See the NCSES Restricted-Use Data Licensing and Procedures page to learn more.

Data Products

Publications.

Data from the NSCG are published in NCSES InfoBriefs and data tables, available at https://www.nsf.gov/statistics/srvygrads/ .

Information from this survey is also included in Science and Engineering Indicators and Women, Minorities, and Persons with Disabilities in Science and Engineering .

Electronic access

The NSCG public use data through 2021 are available in the SESTAT data tool and in downloadable files through the NCSES data page . Data from 1993 to 2019 (2021 forthcoming) are also available in the new NCSES interactive data tool . The NSCG restricted use data are available through the Census Bureau’s Federal Statistical Research Data Centers .

Technical Notes

Survey overview, data collection and processing methods, data comparability and changes, definitions.

Purpose. The National Survey of College Graduates (NSCG) provides data on the characteristics of the nation’s college graduates, with a focus on those in the science and engineering (S&E) workforce. It samples individuals who are living in the United States during the survey reference week, have earned at least a bachelor’s degree, and are younger than 76. By surveying college graduates in all academic disciplines, the NSCG provides data useful in understanding the relationship between college education and career opportunities, as well as the relationship between degree field and occupation.

The NSCG is designed to provide demographic, education, and career history information about college graduates and to complement another survey conducted by the National Center for Science and Engineering Statistics (NCSES): the Survey of Doctorate Recipients (SDR, https://www.nsf.gov/statistics/srvydoctoratework/ ). These two surveys share a common reference date, and they use similar questionnaires and data processing guidelines.

These technical notes provide an overview of the 2021 NSCG. Complete details are provided in the 2021 NSCG Methodology Report, available upon request from the NSCG Survey Manager.

Data collection authority. The information collected in the NSCG is solicited under the authority of the National Science Foundation Act of 1950, as amended, and the America COMPETES Reauthorization Act of 2010. The Census Bureau collects the NSCG data, on behalf of NCSES, under the authority of Title 13, Section 8 of the United States Code. The Office of Management and Budget control number is 3145-0141.

Survey contractor. Census Bureau.

Survey sponsor. NCSES.

Frequency. Biennial.

Initial survey year. 1993.

Reference period. The week of 1 February 2021.

Response unit. Individual.

Sample or census. Sample.

Population size. Approximately 68.6 million individuals.

Sample size. Approximately 164,000 individuals.

Target population. The NSCG target population includes individuals who meet the following criteria:

• Earned a bachelor’s degree ​ Bachelor’s degrees include equivalent undergraduate academic degrees awarded by colleges and universities in countries that may name their degrees differently. Bachelor’s degrees include equivalent undergraduate academic degrees awarded by colleges and universities in countries that may name their degrees differently. Bachelor’s degrees include equivalent undergraduate academic degrees awarded by colleges and universities in countries that may name their degrees differently. or higher prior to 1 January 2020
• Are not institutionalized and reside in the United States or Puerto Rico as of 1 February 2021
• Are younger than 76 years as of 1 February 2021

Sampling frame . Using a rotating panel design, the 2021 NSCG includes new sample cases from the 2019 American Community Survey (ACS) and returning sample cases from the 2019 NSCG.

The NSCG sampling frame for new sample cases included the following eligibility requirements:

• Were residing in the United States or Puerto Rico as of the ACS interview date
• Were noninstitutionalized as of the ACS interview date
• Had earned at least a bachelor’s degree as of the ACS interview date
• Would be under the age of 76 as of 1 February 2021
• Did not have an inaccurate name or incomplete address on the ACS data file

Returning sample cases from the 2019 NSCG originated from three different frames (the 2013 ACS, 2015 ACS, and 2017 ACS) and had the following eligibility requirements:

• Were a complete interview or temporarily ineligible during their initial NSCG survey cycle
• During the 2019 NSCG survey cycle, did not refuse to participate and request to be excluded from future NSCG cycles

Sample design . The NSCG sample design is cross-sectional with a rotating panel element. As a cross-sectional study, the NSCG provides estimates of the size and characteristics of the college graduate population for a point in time. As part of the rotating panel design, every new panel receives a baseline survey interview and three biennial follow-up interviews before rotating out of the survey.

The NSCG uses a stratified sampling design to select its sample from the eligible sampling frame. In the new sample, cases were selected using systematic probability proportional to size (PPS) sampling. ​ With PPS sampling, the probability of selection was proportional to the ACS final person-level weight, adjusted to account for imputed educational attainment, incomplete addresses, or invalid names. With PPS sampling, the probability of selection was proportional to the ACS final person-level weight, adjusted to account for imputed educational attainment, incomplete addresses, or invalid names. With PPS sampling, the probability of selection was proportional to the ACS final person-level weight, adjusted to account for imputed educational attainment, incomplete addresses, or invalid names. Among the returning sample, all eligible cases were selected. The sampling strata were defined by the cross-classification of the following four variables:

As has been the case since the 2013 NSCG, the 2021 NSCG includes an oversample of young graduates to improve the precision of estimates for this important population. The 2021 NSCG includes approximately 164,000 sample cases drawn from the following:

• Returning sample from the 2019 NSCG who were originally selected from the 2013 ACS

Data collection . The data collection period lasted approximately 7 months (8 April 2021 to 1 November 2021). The NSCG used a trimodal data collection approach: self-administered online survey (Web), self-administered paper questionnaire (via mail), and computer-assisted telephone interview (CATI). Individuals in the sample generally were started in the Web mode, depending on their available contact information and past preference. After an initial survey invitation, the data collection protocol included sequential contacts by postal mail, e-mail, and telephone that ran throughout the data collection period. At any time during data collection, sample members could choose to complete the survey using any of the three modes. Nonrespondents to the initial survey invitation received follow-up contacts via alternate modes.

Quality assurance procedures were in place at each data collection step (e.g., address updating, printing, package assembly and mailing, questionnaire receipt, data entry, CATI, coding, and post-data collection processing).

Mode . About 89% of the participants completed the survey by Web, 7% by mail, and 4% by CATI.

Response r ates . Response rates were calculated on complete responses, that is, from instruments with responses to all critical items. Critical items are those containing information needed to report labor force participation (including employment status, job title, and job description), college education (including degree type, degree date, and field of study), and location of residency on the reference date. The overall unweighted response rate was 67%; the weighted response rate was 65%. Of the roughly 164,000 persons in the 2021 NSCG sample, 106,279 completed the survey.

Data e diting. Response data had initial editing rules applied relative to the specific mode of capture to check internal consistency and valid range of response. The Web survey captured most of the survey responses and had internal editing controls where appropriate. A computer-assisted data entry (CADE) system was used to process the mailed paper forms. Responses from the three separate modes were merged for subsequent coding, editing, and cleaning necessary to create an analytical database.

Following established NCSES guidelines for coding NSCG survey data, including verbatim responses, staff were trained in conducting a standardized review and coding of occupation and education information, certifications, “other/specify” verbatim responses, state and country geographical information, and postsecondary institution information. For standardized coding of occupation (including auto-coding), the respondent's reported job title, duties and responsibilities, and other work-related information from the questionnaire were reviewed by specially trained coders who corrected respondents’ self-reporting errors to obtain the best occupation codes. For standardized coding of field of study associated with any reported degree (including auto-coding), the respondent’s reported department, degree level, and field of study information from the questionnaire were reviewed by specially trained coders who corrected respondents’ self-reporting errors to obtain the best field of study codes.

Imputation. Logical imputation was primarily accomplished as part of editing. In the editing phase, the answer to a question with missing data was sometimes determined by the answer to another question. In some circumstances, editing procedures found inconsistent data that were blanked out and therefore subject to statistical imputation.

The item nonresponse rates reflect data missing after logical imputation or editing but before statistical imputation. For key employment items—such as employment status, sector of employment, and primary work activity—the item nonresponse rates ranged from 0.0% to 1.1%. Nonresponse to questions deemed sensitive was higher: nonresponse to salary and earned income was 5.4% and 7.8%, respectively, for the new sample members and 4.7% and 6.8%, respectively, for the returning members. Personal demographic data of the new sample members had variable item nonresponse rates, with sex at 0.00%, birth year at 0.04%, marital status at 0.6%, citizenship at 0.4%, ethnicity at 1.4%, and race at 3.1%. The nonresponse rates for returning sample members were 0.8% for marital status and 0.7% for citizenship.

Item nonresponse was typically addressed using statistical imputation methods. Most NSCG variables were subjected to hot-deck imputation, with each variable having its own class and sort variables chosen by regression modeling to identify nearest neighbors for imputed information. For some variables, there was no set of class and sort variables that was reliably related to or suitable for predicting the missing value, such as day of birth. In these instances, random imputation was used, so that the distribution of imputed values was similar to the distribution of reported values without using class or sort variables.

Imputation was not performed on critical items or on verbatim-based variables. In addition, for some missing demographic information, the NSCG imported the corresponding data from the ACS, which had performed its own imputation.

Weighting. Because the NSCG is based on a complex sampling design and subject to nonresponse bias, sampling weights were created for each respondent to support unbiased population estimates. The final analysis weights account for several factors, including the following:

• Overlap procedures to convert weights that reflect the population of each individual frame (2013 ACS, 2015 ACS, 2017 ACS, and 2019 ACS) into a final sample weight that reflects the 2021 NSCG target population

The final sample weights enable data users to derive survey-based estimates of the NSCG target population. The variable name on the NSCG public use data files for the NSCG final sample weight is WTSURVY.

Variance estimation. The successive difference replication method (SDRM) was used to develop replicate weights for variance estimation. The theoretical basis for the SDRM is described in Wolter (1984) and in Fay and Train (1995). As with any replication method, successive difference replication involves constructing numerous subsamples (replicates) from the full sample and computing the statistic of interest for each replicate. The mean square error of the replicate estimates around their corresponding full sample estimate provides an estimate of the sampling variance of the statistic of interest. The 2021 NSCG produced 320 sets of replicate weights.

Disclosure protection. To protect against the disclosure of confidential information provided by NSCG respondents, the estimates presented in NSCG data tables are rounded to the nearest 1,000.

Data table cell values based on counts of respondents that fall below a predetermined threshold are deemed to be sensitive to potential disclosure, and the letter “D” indicates this type of suppression in a table cell.

Sampling error. NSCG estimates are subject to sampling errors. Estimates of sampling errors associated with this survey were calculated using replicate weights. Data table estimates with coefficients of variation (that is, the estimate divided by the standard error) that exceed a predetermined threshold are deemed unreliable and are suppressed. The letter “S” indicates this type of suppression in a table cell.

Coverage error. Coverage error occurs in sample estimates when the sampling frame does not accurately represent the target population and is a type of nonsampling error. Any missed housing units or missed individuals within sample households in the ACS would create undercoverage in the NSCG. Additional undercoverage errors may exist because of self-reporting errors in the NSCG sampling frame that led to incorrect classification of individuals as not having a bachelor's degree or higher when in fact they held such a degree.

Nonresponse error. The weighted response rate for the 2021 NSCG was 65%; the unweighted response rate was 67%. Analyses of NSCG nonresponse trends were used to develop nonresponse weighting adjustments to minimize the potential for nonresponse bias in the NSCG estimates. A hot deck imputation method was used to compensate for item nonresponse.

Measurement error. The NSCG is subject to reporting errors from differences in interpretation of questions and by modality (Web, mail, CATI). To reduce measurement errors, the NSCG questionnaire items were pretested in focus groups and cognitive interviews.

Data comparability. Year-to-year comparisons of the nation’s college-educated population can be made among the 1993, 2003, 2010, 2013, 2015, 2017, 2019, and 2021 survey cycles because many of the core questions remained the same. Since the 1995, 1997, 1999, 2006, and 2008 surveys do not provide full coverage of the nation’s college-educated population, any comparison between these cycles and other cycles should be limited to those individuals educated or employed in S&E fields.

Small but notable differences exist across some survey cycles, however, such as the collection of occupation and education data based on more recent taxonomies. Also, because of the use of different reference months in some survey cycles, seasonal differences may occur when making comparisons across years. Thus, use caution when interpreting cross-cycle comparisons.

There is overlap in the cases included in the 2010 NSCG through the 2017 NSCG, in the 2013 NSCG through the 2019 NSCG, and in the 2015 NSCG through the 2021 NSCG (see figure 1 ). The overlap among cases allows for longitudinal analysis of a subset of the NSCG sample using restricted use data files within NCSES’ Secure Data Access Facility (SDAF). Cases can be linked across survey years using a unique identification variable and single-frame weights are available for each survey year, allowing for the evaluation of estimates from each frame independently. If you are interested in applying for a license to access restricted use NSCG data via the SDAF, please visit NCSES Restricted-Use Data Procedures Guide . Moreover, the Census Bureau offers NSCG restricted use data files that include a few additional data elements. These files can be accessed via the Federal Statistical Research Data Centers .

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Rotating panel design and sample sizes for the National Survey of College Graduates: 2010–21

ACS = American Community Survey; NSCG = National Survey of College Graduates; NSRCG = National Survey of Recent College Graduates.

During a panel’s second survey cycle (in which it is part of the returning sample for the first time), its members include individuals who responded or who were temporarily ineligible during the first cycle. During a panel’s third and fourth cycles, its members include all respondents, nonrespondents, and temporarily ineligible cases from the preceding cycle. Beginning in 2013, the NSCG transitioned to a design that includes an oversample of young graduates to improve the precision of estimates for this important population.

National Center for Science and Engineering Statistics, National Science Foundation, National Survey of College Graduates.

Changes in survey coverage and population . None.

Changes in q uestio n naire

• 2021. To gauge the effects of the coronavirus pandemic on employment, the content of the NSCG questionnaire was modified for 2021 in two ways:
• The response options of long-standing items were revised to identify pandemic-related consequences: for example, reasons for not working, reasons for working part time, reasons for changing employment, and available job benefits.
• New items were added to understand the effects of the pandemic on salaries and earnings and to measure the prevalence of telework.
• 2019. The content of the 2019 NSCG questionnaire remained unchanged from the 2017 NSCG version.
• 2017. The 2017 NSCG questionnaire added two new questions about U.S. military veteran status that are asked on the ACS.
• 2015. The 2015 NSCG questionnaire added a section on professional certifications and licenses.
• 2013. The 2013 NSCG questionnaire added questions about attendance at community colleges, amounts borrowed to finance undergraduate and graduate degrees, and sources of financial support for undergraduate and graduate degrees. The 2013 questionnaire also differed from the 2010 questionnaire by splitting the first response category for the indicator of sample member location on the survey reference date into two categories. “United States, Puerto Rico, or another U.S. territory” became “United States or Puerto Rico” and “Another U.S. territory.”
• 2010. The 2010 NSCG questionnaire added items on components of job satisfaction, importance of job benefits, year of retirement, whether employer is a new business, and degree of difficulty concentrating, remembering, or making decisions.

Changes in reporting procedures or classification

• In past years, NSCG data were combined with data from the SDR and the NSRCG to form the Scientists and Engineers Statistical Data System (SESTAT). The last series of tables produced from SESTAT used 2013 NSCG data. Since then, NSCG data have been used in numerous tables for NCSES’s two congressionally mandated reports ( Science and Engineering Indicators and Women, Minorities, and Persons with Disabilities in Science and Engineering ).

Field of degree. NSCG respondents are asked to report each degree they have earned at the bachelor’s level or higher, along with the major field of study for each degree. The 2021 NSCG used a taxonomy of 142 “detailed” fields of study from which respondents could select the field that best represented their major. These 142 “detailed” fields of study were aggregated into 31 “minor” fields, 7 “major” fields, and 3 “broad” fields (S&E, S&E-related, and non-S&E). (See technical table A-1 for a list and classification of fields of study reported in the NSCG.)

Full-time and part-time employment. Full-time (working 35 hours or more per week) and part-time (working less than 35 hours per week) employment status is for the principal job only and not for all jobs held in the labor force. For example, an individual who works part time in his or her principal job but full time in the labor force would be tabulated as part time.

Highest degree level. NSCG respondents report the degrees they have earned at the bachelor’s level (e.g., BS, BA, AB), master’s level (e.g., MS, MA, MBA), and doctorate level (e.g., PhD, DSc, EdD), as well as other professional degrees (e.g., JD, LLB, MD, DDS, DVM). Because the NSCG is focused on the S&E workforce, the sampling strategy does not include a special effort to collect professional degrees. As such, there is not always sufficient data for the professional degrees to be displayed separately in the tables.

Occupation data. The occupational classification of the respondent was based on his or her principal job (including job title) held during the reference week—or on his or her last job held, if not employed in the reference week (survey questions A5 and A6 as well as A16 and A17). Also used in the occupational classification was a respondent-selected job code (survey questions A7 and A18). (See technical table A-2 for a list and classification of occupations reported in the NSCG.)

Race and ethnicity. Ethnicity is defined as Hispanic or Latino or not Hispanic or Latino. Values for those selecting a single race include American Indian or Alaska Native, Asian, Black or African American, Native Hawaiian or Other Pacific Islander, and White. Those persons who report more than one race and who are not of Hispanic or Latino ethnicity also have a separate value.

Salary. Median annual salaries are reported for the principal job, rounded to the nearest $1,000, and computed for individuals employed full time. For individuals employed by educational institutions, no accommodation was made to convert academic year salaries to calendar year salaries.

Sector of employment. Employment sector is a derived variable based on responses to questionnaire items A13, A14, and A15. In the data tables, the category 4-year educational institution includes 4-year colleges or universities, medical schools (including university-affiliated hospitals or medical centers), and university-affiliated research institutes. Two-year and pre-college institutions include community colleges, technical institutes, and other educational institutions (which respondents reported verbatim in the survey questionnaire). For-profit business or industry includes respondents who were self-employed in an incorporated business. Self-employed includes respondents who were self-employed or were a business owner in a non-incorporated business.

Fay RE, Train GF. 1995. Aspects of Survey and Model-Based Postcensal Estimation of Income and Poverty Characteristics for States and Counties. American Statistical Association Pro cee dings of the S ec tion on Go ve rnm e nt Statisti c s , 154–59.

Wolter K. 1984. An Investigation of Some Estimators of Variance for Systematic Sampling. J ournal of the Am e ri c an Statisti c al Asso c iation 79(388):781–90.

Technical Tables

Questionnaires, view archived questionnaires, key data tables.

Recommended data tables

Fields of study of college graduates

Occupations of college graduates, college graduates over time, data tables, work activities and job satisfaction of employed college graduates, median salaries of full-time employed college graduates, demographic characteristics of college graduates, general notes.

The National Survey of College Graduates, conducted by the National Center for Science and Engineering Statistics within the National Science Foundation, is a repeated cross-sectional biennial survey that collects information on the nation’s college-educated workforce. This survey is a unique source for examining the relationship between degree field and occupation, as well as for examining other characteristics of college-educated individuals, including work activities, salary, and demographic information.

Acknowledgments and Suggested Citation

Acknowledgments, suggested citation.

Lynn Milan of the National Center for Science and Engineering Statistics (NCSES) developed and coordinated this report under the leadership of Emilda B. Rivers, NCSES Director; Vipin Arora, NCSES Deputy Director; and John Finamore, NCSES Chief Statistician. Jock Black (NCSES) reviewed the report.

The Census Bureau, under National Science Foundation interagency agreement number NCSE-2040211, collected and tabulated the data for the NSCG. The statistical data tables were compiled by Greg Orlofsky (Census) and verified by Nguyen Tu Tran (DMI). Data and publication processing support was provided by Devi Mishra, Christine Hamel, Tanya Gore, Joe Newman, and Rajinder Raut (NCSES).

NCSES thanks the college graduates who participated in the NSCG for their time and effort in generously contributing to the information included in this report.

National Center for Science and Engineering Statistics (NCSES). 2022. National Survey of College Graduates: 20 21 . NSF 23-306. Alexandria, VA: National Science Foundation. Available at https://ncses.nsf.gov/pubs/nsf23306/ .

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AI smartphones may soon help monitor chronic wounds from home

The technology, being developed at the University at Buffalo, could aid millions of people, ease busy health care system

By Laurie Kaiser

Release Date: April 25, 2024

BUFFALO, N.Y. – Individuals increasingly can check on their health conditions at home. Devices that measure blood pressure, glucose and blood oxygen levels, for example, enable patients’ providers to make decisions for their care.

In the near future, patients may also be able to monitor their chronic wounds from the comfort of their homes through mobile artificial intelligence (AI) technology being developed at the University at Buffalo.

Wenyao Xu , professor and associate chair in the Department of Computer Science and Engineering , is leading a team that was recently awarded $3 million from the National Institutes of Health for the four-year research project, “Mobile Health Technologies for Assessing Blood Perfusion in Chronic Wounds.”

Approximately 8.2 million Americans suffer from chronic wounds that stem from a multitude of conditions, including diabetes and major surgery. This technology — accessible through a smartphone — will help streamline treatment, Xu said.

“Patients with these conditions frequently visit their health care providers or specialty wound care clinics and, in and some cases, need to be hospitalized,” Xu said. “This can be a financial burden and a time burden to both the patient and the health care system.”

Empowering patients, regardless of income, location

While the new technology will benefit all patients, it will particularly help individuals who have barriers to transportation or who live in rural areas where wound care services are limited or unavailable, he said.

“The approach proposed in this project is innovative,” he said, “because it will explore and validate new mobile computing and data-driven techniques for wound care and blood perfusion assessment based on evidence-based truth.”

The goal is to empower patients by giving them free, usable technology they can download that will provide exact measurements on how the wound is healing — and keep them out of the hospital.

“Chronic wounds often result from poor blood flow to the affected area, which can lead to a lack of oxygen and nutrients necessary for the healing process,” Xu said. “The long-term objective of this project is to improve wound care and impact wound treatment services by developing low-cost technologies that aid with chronic wound treatment and care.”

Other UB researchers on the project are Jun Xia, PhD, professor in the Department of Biomedical Engineering; Linda M. Harris, MD, professor of surgery and chief of UB’s Vascular Surgery Division; Saptarshi Chakraborty, PhD, assistant professor in the Biostatistics Department; Praveen Arany, PhD, associate professor in the Department of Oral Biology; and Heamchand Subryan, MFA, director of interaction design at the Center for Inclusive Design and Environmental Access (IDEA Center) at UB. They are also working with a research team at NEC Laboratories America , based in Princeton, N.J.

“We are engaging with an industry partner early on to pave the way for mass production of this technology,” Xu said.

Combining AI and mobile optics

The research began about five years ago, stemming from a conversation Xu had with Xia on how to advance AI and mobile optics together – mobile AI – to improve health care, Xu explained.

“We then connected with Dr. Harris, a professor of surgery at UB who has a specialty in vascular surgery,” Xu said. “This is an underexplored area for advanced mobile AI technology.”

Currently, they are collaborating with vascular clinics in the UBMD Physicians’ Group where the team recruits patients in the technology evaluation and clinical study.

“The AI technology analyzes the mobile images and predicts if the wound is on the right track for healing,” Xu said. “If it’s not, the patients can make an appointment to see the doctor.”

First stage: fine-tuning technology

The work with the clinics is the first in a two-stage process and will focus on fine-tuning the prototype and determining what needs to be improved over the next two years. It will involve more than 200 participants in Western New York.

“We will build upon this work to enhance a commodity smartphone with a low-cost multispectral imaging sensor. An app will be available to download on users’ phones to obtain perfusion-related measures,” Xu said. “We are developing machine learning algorithms that extracted the biomarkers of healing and rigorously assess the tools for usability.”  

In early 2026, the team will implement the second stage: a participatory design, feedback and usability study that will include patients and human-computer interaction experts to assess and improve the technology’s usability.

The hope is that eventually anyone who is suffering from a chronic wound can access this technology, he said.

“This AI technology has the potential to advance the current standard of wound care for recovery after discharge from clinical therapies,” he said. “These contributions are significant because they can extend the health self-management of our society through proactive health care and real-time intervention and reduce subjective bias and financial burden for patients, their caregivers and society.”

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Laurie Kaiser News Content Director Dental Medicine, Pharmacy Tel: 716-645-4655 [email protected]