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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 4 hours ago
for new funding sources, publishing and presenting research topics as applicable. Candidates are expected to have strong publication record in biomolecular modeling and computational biophysics/chemistry
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Deadline 26 Apr 2026 - 00:00 (UTC) Country Ireland Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related
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2026 Is the job funded through the EU Research Framework Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The selected person will
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and medicine. The key objective is to support efforts to advance biomedical research using computational methods. For more details, please view https://www.ntu.edu.sg/medicine/research/research
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that accelerate innovation in healthcare and biotechnology through validation, engineering, and valorization pathways such as licensing, partnerships, and spin‑outs. About the role We are seeking a Computational
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funded through the EU Research Framework Programme? Other EU programme Reference Number P568286 Is the Job related to staff position within a Research Infrastructure? No Offer Description A call for
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Your Job: We are looking for a PhD student to develop learning-based surrogate models for predicting stress fields in patient-specific arteries. Especially high stresses in plaque can lead to
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-performance computing resources suitable for large-scale machine-learning and foundation-model experiments. Your role We are seeking a highly motivated Postdoctoral Researcher to join the FNR AI-HPC 2025
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. • Working with large-scale HR and workforce data models in Scuba. • Supporting high-visibility reporting that impacts funding retention and workforce strategy. • Translating program data into actionable
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(e.g. Interspeech, ICASSP, SSW) and contribute to open-source release of corpus and models. Qualifications Requirements A doctoral degree in speech technology, machine learning, computational linguistics