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Field
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Python, MATLAB, or C++. Experience with machine learning techniques, CAD, computational modeling, 3D printing, motion capture, and/or material testing. Proficiency in programming languages commonly used in
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of mutual interest such as, but not limited to, automatic machine learning model selection and automatically explaining machine learning classification / prediction results. The Luo lab is in UW Medicine’s
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to implement advanced computational pipelines, including machine learning, deep learning, Bayesian inference, and probabilistic mixed membership modeling for innovative research. · Contribute
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the HNSCC team, including Taran Gujral (machine learning-enabled drug screening), Slobodan Beronja (mouse models of HNSCC), and Patrick Paddison (functional genomics). This work will encompass a broad array
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or experience in nontraditional research publication methods and collaborative notetaking software (e.g., Roam Research, Obsidian, Notion). ? Familiarity with cloud computing and machine learning techniques
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and interventional datasets in high dimensions. Our interdisciplinary approach integrates interpretable machine learning, statistics, algorithms, and single-cell multi-omics. Position Overview You will
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policies pertaining to other schools at Duke University. The postdoc candidate is expected to: 1) Develop novel methods for incorporating scientific machine learning in solving problems in solid mechanics
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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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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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this team, you will obtain hands-on training and experience in developing state-of-the-art machine learning and AI models on these platforms while contributing extensively to discovering novel lead molecules