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Cornell University

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Multiple Engineering Education Research Postdoctoral Positions within Cornell’s Duffield College of Engineering Cornell University in United States

Degree Level

Postdoc

Field of study

Computer Science

Funding

Available

Deadline

Nov 16, 2026

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Country

United States

University

Cornell University

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Keywords

Computer Science
Education
Psychology
Electrical Engineering
Materials Science
Critical Thinking
Higher Education
Curriculum Development
Qualitative Method
Measurement And Validation
Statistics
Physics
Psychometric

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Posted Yesterday

About this position

Cornell University’s newly established Duffield Engineering Education Research Institute is recruiting multiple postdoctoral associates to work across a set of education research projects within the College of Engineering. The posts sit in a growing institute focused on how engineers learn, how engineering identities and knowledge develop, and how educational systems can be redesigned to support meaningful learning. Successful candidates will join a collaborative research environment with structured mentorship and opportunities to contribute to collaborative publications and evidence-based practice.

One project centers on the IMPACT Portal, an initiative to make validated measurement instruments more accessible to instructors and researchers. The postdoctoral researcher will help build the portal by working with instructors, students, researchers, and administrators to identify needs, gather instruments, and develop ways to communicate validity evidence and support use across courses and institutions.

A second project, MARQUIS, develops a quantum course-based undergraduate research experience to broaden access to authentic quantum engineering research. The postdoctoral researcher will help translate technical datasets into student learning activities, develop instructional materials and assessments, and study education, training, and workforce development efforts in a quantum education setting.

A third project explores how generative AI is reshaping engineering teaching and learning. The postdoctoral researcher will work as an embedded education researcher with faculty to turn teaching ideas into researchable questions, design assessments, coordinate data collection, and compare outcomes across disciplinary course contexts.

The fourth project investigates AI-supported reflection and critical thinking across physics, biology, and engineering courses using the Automated Critical Thinking Reflection tool. The postdoctoral researcher will contribute to prompt design, survey and response workflows, qualitative and quantitative analysis, and evaluation of AI-assisted coding methods in collaboration with participating instructors and the research team.

Across projects, the institute emphasizes collaboration with faculty and practitioners, research translation, and development of tools and resources that can be used beyond Cornell.

Funding details

Available

What's required

A PhD or near completion is required, with preferred backgrounds varying by project: engineering education, educational measurement, educational or social psychology, science education, learning sciences, higher education, a relevant STEM field, or related disciplines. Strong candidates should have experience with qualitative and quantitative research methods, psychometric or survey analysis where relevant, clear communication, sound data management, human subjects research experience, and for some projects technical expertise in quantum information science, semiconductor research, materials science, applied physics, engineering physics, or generative AI/large language models. Some projects also prefer experience with assessment development, validation frameworks, facilitation, curriculum or teaching collaboration, and reproducible programming in R, Python, MATLAB, Mplus, or similar tools.

How to apply

Submit a cover letter stating which projects interest you and why, your goals for the postdoc, how your background fits the requirements, and your anticipated start date. Upload a CV including publication list, Ph.D. graduation date or expected date, and your Ph.D. advisor’s name. Provide the names of 2-3 recommenders for possible reference checks after initial screening.

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