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Postdoc Position (f/m/d) for any of the following topics: Combining non-equilibrium alchemistry with machine learning Free energy calculations for enzyme design Permeation and selectivity mechanisms in
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 8 days ago
. Education: We prepare tomorrow`s healthcare professionals and biomedical researchers from all backgrounds by facilitating learning within innovative and integrated curricula and team-oriented
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science. You will be part of a dynamic research group with expertise in Earth Observation, geoinformatics, and machine learning, offering an excellent environment for advancing your research and building
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profile: The ideal candidate will have: A PhD in biology, cognitive science, or an adjacent field (e.g. biomedicine, computer sciences); A strong academic track record, including high-quality publications
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statistical evaluation Machine learning analyses: implementation of established and new workflows Coordination of activities with Consortium partners, including presentation of results at consortium meetings
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the Division of Data Science and Artificial Intelligence and the employment is with Chalmers University of Technology. The division’s research spans from foundational machine learning theory to applications
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statistical or machine learning methods to complex datasets. Evidence of involvement in grant writing or development of independent research ideas. A commitment to teaching the next generation of researchers
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Research Associate. The Goodwill Computer Lab researches on a variety of computer systems topics including HPC resilience, data center power management, large-scale job scheduling and performance tuning
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or junior graduate students. A formal training, education, or certification in a secondary area (beyond the main PhD focus) such as additive manufacturing, advanced/hybrid manufacturing, machine learning
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statistical or machine learning methods to complex datasets. Evidence of involvement in grant writing or development of independent research ideas. A commitment to teaching the next generation of researchers