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Conrad Borchers

Assistant Professor of Artificial Intelligence in Education, Policy, and Organizations

Vanderbilt University

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Statistics

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Statistical Inference

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Psychology

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Education

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Network Analysis

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Information Technology

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Positions1

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Conrad Borchers

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Vanderbilt University

Postdoctoral Scholars in AI, Learning Analytics, and Educational Data Mining at Vanderbilt University

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 c.borchers@vanderbilt.edu.