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design and causal inference (including virtual lab experiments); and/or (4) network or computational modeling. The ideal candidate will have a strong interest in applying these tools to questions of group
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GROMACS, AMBER, MARTINI, OpenMM, or similar tools ii) Experience with machine learning or AI experience (e.g., PyTorch, JAX) for RNA modeling and/or drug discovery iii) Experience in coding and scripting
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mesoscale fractal geometry, creating physics-informed neural network models to analyze turbulent structures, and comparing simulation results to astronomical observations to develop methods for inferring
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when extending an offer. The ideal candidates will hold a PhD, have multiple years of prior research experience using a model organism, and a track record of peer-reviewed publications. Prior experience
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monitoring. Design and implement machine learning models to analyze multimodal data (e.g., student behavior, engagement, and performance) to enhance personalized learning. Develop and evaluate GPT-powered AI