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modern AI/ML methods to protein and cellular biology, including protein structure prediction, protein–protein and small-molecule–protein docking, cell state prediction from large-scale Perturb-seq datasets
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time Spectroscopic studies of galaxies and AGN at intermediate to high redshift Analysis of JWST slit and/or slitless spectroscopy datasets and/or JWST imaging datasets Development of methods for large
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(https://www.hsph.harvard.edu/lin-lab/ ), Professor of Biostatistics and Professor of Statistics. The postdoctoral fellow will develop and apply statistical, machine learning (ML), and AI methods
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to ambitious research at the intersection of machine learning, neuroscience, and computational biology. This role centers on computational neurobiology and the use of modern AI/ML methods to model brain circuits
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systems at various scales, for example using ab initio electronic structure methods like density-functional theory, developing interatomic potentials with various methodologies including machine learning