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-disciplinary research and development projects related to learning engineering and AI in education, working with a team of postdoctoral researchers, PhD students, and Master’s/undergraduate researchers across
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related to learning engineering and AI in education, working with a team of postdoctoral researchers, PhD students, and Master’s/undergraduate researchers across multiple universities and organizations
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Associate as part of Cornell’s Active Learning Initiative (https://teaching.cornell.edu/active-learning-initiative-0) for the AYs 2026 – 2028. We invite applications from candidates with a specialization in
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moves. Success will be measured by having published or contributed to papers in top venues (e.g., Nature Science of Learning, Computers and Education, ACM Learning at Scale, Educational Data Mining) and
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Postdoctoral Associate as part of Cornell’s Active Learning Initiative for the AYs 2026 – 2028. We invite applications from candidates with a specialization in any area of History of Art broadly defined, and
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in Ithaca, NY with a focus on developing deep learning algorithms. Dr. Haiyuan Yu, Ph.D. is a Tisch University Professor of Computational Biology in the College of Agriculture and Life Sciences and a
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the appointment start date; demonstrate strong expertise in computational biology or data-driven modeling, with experience in one or more of the following areas: machine learning or deep learning, structural
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this diversity. Our research spans comparative genomics, chromatin architecture, gene expression, protein abundance, and metabolite profiling—combined with computational biology, machine learning, and advanced
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Associates will teach one seminar per year, which is one section of SHUM 2750 Introduction to the Humanities in the spring term. As well, we expect each to supervise the one-credit course SHUM 4750 for guiding
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systems architecting AI/ML-driven clinical and operational decision support Digital health and learning health systems Healthcare operations, resource allocation, and workflow optimization Network, graph