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applications for a PhD Student or 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
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machine learning approaches. These are similar to earlier work on charge and excitation energy transfer (see https://constructor.university/comp_phys). The project for the PhD fellowship is slightly more
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and data analytics (including machine learning and deep learning); from high-performance computing to high-performance analytics; from data integration to data-related topics such as uncertainty
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of German, or willingness to learn, is desirable since the position involves undergraduate teaching, e.g., exercise sessions TUD strives to employ more women in academia and research. We therefore expressly
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machine learning We offer: Academic freedom to pursue your scientific interests related to infection biology, inflammation, gene expression, and intracellular organization Competitive salary including
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the official DAAD template [doc-Datei] and ask your professors to email the confidential document to the GSPoL (admissions.gspol at uni-muenster.de ). Step 2: personal interview at the GSPoL Step 3
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existing methodologies. Carry out literature review, hypothesis development, and experimental design. Adapt, develop and learn new tools, software, and methodologies independently. Present and publish
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literature review, hypothesis development, and experimental design. Adapt, develop and learn new tools, software, and methodologies independently. Present and publish research in both academic and non-academic
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. Adapt, develop and learn new tools, software, and methodologies independently. Present and publish research in both academic and non-academic audiences. Attend and participate in academic and non-academic
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direction (possibly forming spontaneous “lanes”), crossing, and opposite flows. For single-lane vehicular traffic, the model should revert to a car-following model. In cooperation with the supervisor Dr