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methods for whole genome/exome sequencing, RNA-seq, ATAC-seq, single cell and spatial datasets. The successful candidate will interact closely with other computational and experimental biologists and
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the products and services of partner organizations; and (c) general purpose research on methods, processes, and practices that support the development and scaling of technologies such as digital education
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of experiments and outcomes. Apply the theories and methods of a life science discipline to interpret and perform analyses of experiment results; offer suggestions regarding modifications to procedures and
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at unprecedented scales. Our goal is to create highly scalable experimental approaches that enable machine learning methods to predict the structure and properties of RNA-protein complexes. We employ sophisticated
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in lab and/or field based on knowledge of scientific theory. Independently conduct experiments; maintain detailed records of experiments and outcomes. Apply the theories and methods of a life science
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on knowledge of scientific theory. * Independently conduct experiments; maintain detailed records of experiments and outcomes. * Apply the theories and methods of a life science discipline to interpret and
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common equipment, and also have the benefit of access to research facilities at Stanford University including core computing, microscopy, library, biostores, and analytical facilities. The Spin lab has
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methods to improve prediction model generalizability, model fairness, and generalizability of fairness across different clinical sites. The researcher will have the opportunity to use machine learning and
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manage program(s) or function(s) under minimal supervision. Administer, implement, and interpret university and department policies and procedures on issues regarding admission, financial aid, housing
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The Stanford Abdominal Diffusion Group is seeking thoughtful, motivated and collaborative postdoctoral fellows to join a growing team developing motion-robust multi-shot DWI methods for liver, pancreatic, and