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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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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
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that make a more just and resilient future. The Postdoctoral Associate will have the opportunity to align with the most relevant academic department in the College of Architecture, Art, and Planning and teach
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opportunity to align with the most relevant academic department in the College of Architecture, Art, and Planning and teach one course per year subject to department needs. The Postdoctoral Associate will be a
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and as a part of a collaborative team Values mentorship and training Orientation towards learning How to Apply Please send your application to Tara Fischer at tdf45@cornell.edu . Your application should
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, nutrition lesson) and bi-weekly they will engage in a self-guided culinary session at home (prepare an ethnic, plant-based meal). To learn more visit https://www.aceprogramnyc.com/ . 2) The Double Up Foods
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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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comparative genomics, chromatin architecture, gene expression, protein abundance, and metabolite profiling—combined with computational biology, machine learning, and advanced statistical methods. Supported by