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Field
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. MATLAB, C/C++, Python. Highly motivated and keen on working in an international and interdisciplinary team. Applicants with strong background in the following fields are preferred: Machine Learning Formal
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 12 hours ago
Lab at UNC-Chapel Hill is seeking a highly motivated Postdoctoral Research Fellow to join our group at the intersection of statistical methodology, machine learning, and biomedical data science. Our
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the car at home; A great opportunity in a specialized hospital where you can also continue to learn and grow yourself if you wish: the AVL Academy offers innovative and inspiring education in the field
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measurements from real projects, statistically analyse them, and conduct experiments with modern machine learning techniques and generative AI. A strong background in software engineering as well as some
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 4 days ago
universities in the nation for federal research expenditures as well as for federally funded social and behavioral sciences research and development. Here at Carolina, our highly skilled postdocs play a vital
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learning, and computer graphics. The positions are fully-funded with payments and benefits according to German public service positions (TV-L E13, 100% for PhDs and TV-L E14, 100% for PostDocs; 45k – 57k
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: lattice gauge theory Lattice Field Theory Machine Learning / Machine Learning Nuclear Theory Nuclear astrophysics Appl Deadline: 2026/02/01 11:59PM (posted 2025/11/04) Position Description: Apply
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. Experience with machine learning is highly preferred. Ability to work independently and as part of a team. Key Requirements for PhD: Hold a Bachelor's degree with outstanding performance in Physics or related
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development in large multi-site cohorts; and 3) developing advanced machine learning models of task-related brain function. The fellow will have the opportunity to contribute to these projects and will also be
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ESSENCE: Efficient Self-Supervised Machine Learning for Adaptive Wireless Communication Systems This project investigates self-supervised learning (SSL) for wireless communication systems to improve