188 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at Princeton University
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successful candidate will develop and apply computational approaches to chemical datasets, with artificial intelligence/machine learning (AI/ML) being a major focus. Many of the laboratory's interests center
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
: 277494287 Position: Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning Description: The Atmospheric and Oceanic Sciences Program at Princeton University, in
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] Subject Areas: Artificial Intelligence, Machine Learning and Autonomy Computational Science and Engineering / Machine Learning Computational Biology / Data Analytics Analytical Chemistry / Current
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computational biology/chemistry, machine-learning for biological or chemical data, and drug discovery/design. Mentorship is taken seriously and every effort will be made to ensure the candidate is able to achieve
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The Program in African Studies (PAS) at Princeton University invites applications for a Postdoctoral Research Associate or more senior research positions for the 2026-2027 academic year. Up to two
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: 278599539 Position: Postdoctoral Research Associate/Research Program in Development Economics (RPDE) Description: The Research Program in Development Economics (RPDE) at Princeton University's School
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emerging technologies such as artificial intelligence, quantum technologies, and space-based systems, including large satellite constellations. A recent PhD in physics, engineering, computer
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The Research Program in Development Economics (RPDE) at Princeton University's School of Public and International Affairs invites applications for two Postdoctoral Research Associate positions
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The James Madison Program in American Ideals and Institutions at Princeton University is dedicated to the pursuit of scholarly excellence in the fields of constitutional law and political thought
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
to develop hybrid models for sea ice that combine coupled climate models and machine learning. Our previous work has demonstrated that neural networks can skillfully predict sea ice data assimilation