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management. Demonstrated ability to independently lead complex technical projects and collaborate across disciplines. Demonstrated expertise in machine learning, deep learning, statistical modeling, and AI
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Essential Functions Include Leadership - 45% Set and promote the agenda to fulfill Cornell Tech’s commitment to deep collaboration with NYC Public Schools to help advance AI and computer science education
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. • Demonstrated ability to independently lead complex technical projects and collaborate across disciplines. • Demonstrated expertise in machine learning, deep learning, statistical modeling, and AI system design
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, deep learning, statistical modeling, and AI system design applied to biological or agricultural systems. Experience architecting scalable AI pipelines, including model evaluation, deployment, 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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, United States of America [map ] Subject Areas: Electrical and Computer Engineering / artificial intelligence , Artificial Intelligence and Machine Learning (AI/ML) Starting Date: 2026/01/01 Salary Range: $62,232-$80,000
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Museum of Art. They will deepen a culture of collaboration and will ensure that Cornell faculty and students, as well as the broader Finger Lakes community, see and utilize the Museum as a vital learning
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well as the broader Finger Lakes community, see and utilize the Museum as a vital learning resource. The Director has primary responsibility for all aspects of the Museum's operation, management, and resources. Working
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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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, and the ability to read related scientific papers on cancer combination therapy. It would also require expertise in relevant AI methodology, such as deep learning architectures for property prediction