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, Astronomy, and Data Science. The initial appointment is for one year, with annual renewal expected for up to three years, subject to satisfactory performance and available funding. The postdoc will be
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 months ago
well as for federally funded social and behavioral sciences research and development. Here at Carolina, our highly skilled postdocs play a vital role in our research enterprise and towards our overall commitment
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Researcher (R4) Positions Postdoc Positions Application Deadline 2 Sep 2026 - 17:00 (Europe/Paris) Country France Type of Contract Permanent Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Jan
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. The Enrico Fermi Institute (EFI) is a multi-disciplinary institute at the University of Chicago that is engaged in research in particle physics, astrophysics, geophysics and accelerator physics. Both
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documentation practices. Experience with GPU-accelerated hardware platforms and software engineering including NVIDIA GPUs and CuPy/CUDA/C++ programming. Familiarity with 5G/6G wireless standards and AI/ML
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initiative on Agentic AI for Scientific Discovery. This project aims to solve a grand challenge in modern AI: developing a deep research assistant capable of accelerating R&D workflows and operations in
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Position Description tl;dr Meta’s AI and Systems Co-design team is looking for candidates for various roles: postdocs and visiting professors, as well as fresh/experienced PhDs. Overview Our org's
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regulatory networks Prioritize targets for validation Enable predictive modeling of neuroimmune interactions Accelerate decision-making and scalability To maximize impact, proposals are encouraged to anchor
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Researcher (R4) Positions Postdoc Positions Application Deadline 2 Sep 2026 - 17:00 (Europe/Paris) Country France Type of Contract Permanent Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Jan
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membrane performance. Therefore, this objective of this research is develop efficient algorithms and models based on deep learning to accelerate the physics simulation for membrane relevant processes, which