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transport of bioaerosols? Then the Department of Environmental Science invites you to apply for a 2 year post doc position, with possibility for extension. The position is associated with two research
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-quality issues in bulk storage and food facilities. You will join and learn from a community of scientists and post-docs in the unit engaged in efforts to integrate and analyze data from volatile-gas
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modeling, molecular interactions/energetics, and tools such as AlphaFold, Rosetta, or MD simulations. Solid programming skills (Python); familiarity with machine learning is a plus. For both profiles, we
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Skip to Main Content Toggle navigation Home Search Jobs Job Alerts Log In /Create Account Help Post Doc Res Assoc Bookmark this Posting Print Preview | Apply for this Job Announcement Details Open
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economy. As a postdoctoral researcher, you will unravel how silicon suppresses liquid copper infiltration at the atomic scale, using density functional theory-accurate machine-learned potentials and
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Functional Theory (DFT)-accurate machine-learned interatomic potential (MLIP), enabling predictive MD simulations capable of resolving atomic-scale LCI mechanisms with near-DFT accuracy Investigate how silicon
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Chekouo and his collaborators within and outside the University of Minnesota. The research will focus on the development of Bayesian statistical/machine learning methods for the data integration analysis
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October 2029. Job description The post doc position focuses on research questions related to data integration and visualisation (e.g. digital twins) at the interface between agricultural and biological
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Veterinärmedizinische Universität Wien (University of Veterinary Medicine Vienna) | Austria | 2 months ago
analysis, machine learning, eye tracking). The main duty of the post-holder will be statistical consulting. A broad knowledge of statistics in this scientific area is required. The applicant should have in
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. Demonstrated expertise in using machine learning and optimization frameworks in conjunction with FE simulations to assist with component and/or process design is preferred. Excellent written and oral