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differentiable programming and physics informed machine learning (Graph Neural Networks and Neural Operators) for solving inverse and optimization problems. Develop AI-accelerated numerical methods for identifying
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for predicting carbon cycle in permafrost. Conduct numerical experiments to explore the coupled physics that lead to permafrost melting and greenhouse gas emissions. Compile and analyze Arctic environmental data
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conferences. Required Qualifications Bachelor’s degree in Biomedical Engineering, Computer Science, Electrical Engineering, Physics, Biology, Neuroscience or related fields. Research interest in physiology and
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condensates in cancer signaling. Research in the Guan lab is at the interface of physics and biology (https://juanguanlab.wixsite.com/biophysics/). The team employs highly interdisciplinary approaches in cell
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) to obtain data for analysis. Assist EPIC staff and clients with Institutional Review Board process and documentation. Conduct quantitative research (e.g., survey design, descriptive statistics, inferential