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Field
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. This position offers an exciting opportunity to work at the intersection of HPC and AI, addressing critical communication bottlenecks and optimizing network interconnects for large-scale distributed systems
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The Özel Lab at the Stowers Institute for Medical Research has openings for postdoctoral researchers to pursue independent projects investigating the gene regulatory networks that control neuronal
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HH-Gli1-Mycn network regulates heart regeneration from newt to human. Nature Communication. 2018 9(1):4237. You will be expected to collaborate with other laboratory scientists and outside scientific
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. Excellent communication skills in English, the ability to work in multi-disciplinary teams, and scientific creativity are essential. NYUAD offers a stimulating research environment led by a distinguished
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state-of-the-art facilities for teaching, research, scholarship, and creative activity. The institution advances a diverse, equitable, and inclusive community where everyone feels connected and valued—and
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Center (OTIC) Washington DC Metro Area. The CCI xG Testbed, led by Dr. Aloizio Da Silva, is looking for motivated and talented researchers with expertise in Cellular Communication Network, Open RAN
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Description Job Responsibilities: 50% - Utilize graphical/network models and data integrations, including work on collaborative projects. 10% - Assist in maintaining and upgrading, as necessary, our server
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)—topics including, but not limited to: · Physics-informed neural networks (PINN) & neural operators · Physics-aware convolutional neural networks (PARC) · Meta-learning/transfer
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transportation networks. In particular, the successful candidate will conduct cutting-edge research in: Adaptive incentive mechanism design for complex sociotechnical systems Strategic learning and equilibrium
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
learning. Our previous work has demonstrated that neural networks can skillfully predict sea ice data assimilation increments, which represent structural model errors (https://doi.org/10.1029/2023MS003757