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Conrad Borchers
4 months ago
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Postdoctoral Scholars in AI, Learning Analytics, and Educational Data Mining at Vanderbilt University Vanderbilt University in United States
Degree Level
Postdoc
Field of study
Computer Science
Funding
Postdoctoral scholar positions, 1-2 openings, with substantial intellectual autonomy, access to large-scale longitudinal educational datasets, multidisciplinary collaborations, support for publications, conference travel, career development, and opportunities to contribute to funding applications. Duration is 1 year, renewable. No stipend amount stated.
Deadline
Expired
Country
United States
University
Vanderbilt University
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Keywords
About this position
Vanderbilt University’s Learning, AI & Pathway Systems (LAPS) Lab is recruiting 1–2 postdoctoral scholars for research at the intersection of AI in education, learning analytics, educational data mining, machine learning, and computational social science.
The postdoctoral scholar will work on projects related to AI-supported tutoring, student pathways, motivation, educational systems, and large-scale learning data. The lab’s research spans computational modeling of educational trajectories, student effort and agency, prerequisite networks, adaptive support systems, tutoring dialogue, and the integration of AI into technology-supported learning environments.
There are two possible research tracks: Track A in the Department of Computer Science focuses on computational models of AI, educational systems, and student pathways; Track B in the Department of Leadership, Policy, and Organizations focuses on AI-supported tutoring and goal setting, including randomized field experiments and motivational interventions. Applicants may indicate interest in one or both tracks.
The position is supervised by Conrad Borchers, Assistant Professor of Artificial Intelligence in Education, Policy, and Organizations at Vanderbilt University. The postdoc will also collaborate with the PLUS Tutoring project at Carnegie Mellon University led by Ken Koedinger.
Required qualifications include a completed Ph.D. by the start date in a relevant field, strong quantitative or computational research experience, evidence of research potential, programming skills such as Python or R, and strong communication and writing skills. Preferred experience includes sequential, longitudinal, or networked data; machine learning or statistical inference; educational, behavioral, or institutional datasets; and theory-building through computational approaches.
The role offers substantial intellectual freedom, interdisciplinary collaboration, access to large-scale longitudinal educational datasets, support for publications and conference travel, and opportunities to help shape a new interdisciplinary research agenda. The appointment is for 1 year, renewable. Applications are reviewed on a rolling basis until the position is filled.
To apply, submit a cover letter, CV, 1–3 representative samples, and contact information for 2–4 academic references. Interested candidates should contact Conrad Borchers at [email protected].
Funding details
Postdoctoral scholar positions, 1-2 openings, with substantial intellectual autonomy, access to large-scale longitudinal educational datasets, multidisciplinary collaborations, support for publications, conference travel, career development, and opportunities to contribute to funding applications. Duration is 1 year, renewable. No stipend amount stated.
What's required
Ph.D. completed by the start date in a relevant field; strong quantitative or computational research background; evidence of research potential through publications, projects, or dissertation work; analytical programming experience such as Python or R; strong communication and writing skills; interest in educational systems, learning, motivation, or human behavior. Preferred: experience with sequential, longitudinal, or networked data; machine learning or statistical inference; prior work with educational, behavioral, or institutional datasets; interest in theory-building through computational approaches; expertise in theories of human learning and motivation; experience collaborating across disciplines and with external stakeholders.
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Professors
Assistant Professor of Artificial Intelligence in Education, Policy, and Organizations
United States
Research Interests
Educational Psychology
Educational Technology
Self-regulated Learning
Peer Tutoring
Student-centered Learning
Professor
United States
Research Interests
Statistics
Computational Modelling
Computer Science
Cognitive Science
Machine Learning
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