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: Durham, North Carolina 27708, United States of America [map ] Subject Area: Engineering / Electrical and Computer Engineering Appl Deadline: (posted 2025/08/04, listed until 2025/08/15) Position
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More Information: Please visit "Why Carnegie Mellon " to learn more about becoming part of an institution inspiring innovations that change the world. Click here to view a listing of employee benefits
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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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by working to develop novel algorithms on finite element method, isogeometric analysis, geometric modeling, machine learning and digital twins to study various applications such as computational
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of the land ice contribution to sea level rise until 2300 with machine learning. You will develop probabilistic machine learning “emulators” of multiple ice sheet and glacier models, based on large ensembles
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terms of research and education, covering all aspects of computer science, including but not limited to algorithms, databases, cloud computing, machine learning, operating systems and security. Jobs
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topics: Free space optical communication Visible light communication DSP for coherent optical communication Machine learning and AI-native physical layer design Optical reconfigurable intelligent surfaces
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of recruiting talent aligned to these values. We are looking for a Postdoctoral Research Fellow who has: a PhD (or in near completion) in the relevant fields of Artificial Intelligence, Machine Learning, HCI
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More Information: Please visit “Why Carnegie Mellon ” to learn more about becoming part of an institution inspiring innovations that change the world. Click here to view a listing of employee benefits
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Python, MATLAB, or C++. Experience with machine learning techniques, CAD, computational modeling, 3D printing, motion capture, and/or material testing. Proficiency in programming languages commonly used in