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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Germany | 20 days ago
AI in biology. The successful candidate will design and implement physics-informed machine learning frameworks and predictive models to uncover how gene expression and mechanical forces interact
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 21 hours ago
HILL, NC Position Location North Carolina, US Hiring Range $40,000 - $42,000 Pay Band Information To learn more about the pay band for this branch and role, please see the Career Banding rates
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algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics, spanning diverse application domains such as medicine, energy systems, biomedical
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established in the areas of electronic and electromagnetic simulation and design, machine learning and artificial intelligence in electrical engineering, electrical low-frequency and high-frequency measurement
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sheet evolution, methane hydrate fluxes, or applying machine learning to geosciences to reconstruct glacial histories and project future ice sheet behavior. Please read this interview for more details
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experience Desirable criteria Up to date knowledge of machine learning methods applied to clinical or omics data Up to date knowledge in long read methylation methods applied to clinical or omics data
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tasks that require coordinated base-arm-hand behaviors in dynamic environments. We seek candidates with a strong background in robotics and machine learning, and demonstrated experience in at least two of
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27 Mar 2026 Job Information Organisation/Company Télécom Paris Research Field Computer science » Computer architecture Researcher Profile First Stage Researcher (R1) Positions Postdoc Positions
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, metals and their surfaces. Machine learning methods are used to close the complexity gap. Currently, the group consists of three full professors, one associate professor, 6 postdocs and about 15 PhD and 7
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, and registry-linked outcome data. In this project, you will develop and apply AI-based methods (e.g. machine learning methods and many other methods) to harmonize historical and current pathogen