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computational analysis of large-scale pharmacogenomic datasets. The lab maintains active collaborations with medicinal chemists, structural biologists, and clinical oncologists at Stanford and elsewhere
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candidate will gain expertise in CRISPR screening, drug sensitivity profiling, target deconvolution, and the computational analysis of large-scale pharmacogenomic datasets. The lab maintains active
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Health Epidemiology and Population Health Health Policy Med: PCOR Neuroscience Institute Medicine, Biomedical Informatics Research (BMIR) Biomedical Data Science Medicine, Center for Digital Health Postdoc
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and experimentalists working across species as part of SCENE The Tolias Lab fuses large‑scale systems neuroscience with machine learning to derive principled models of cortical computation. Our newly
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-omics discovery. The fellow will help develop and apply computational approaches to study heart failure mechanisms and therapeutic targets using large-scale human datasets, including cardiovascular
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connections between the lab, classroom, and society. Required Qualifications: Highly motivated postdoctoral researcher with extensive experience with item response theory models, computer adaptive testing, and
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demonstrated ability to design, train, and deploy large-scale models Expertise in at least one of computer vision, speech recognition, or multimodal learning, with experience in real-world technology deployment
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rational strategies for next-generation therapeutics. The Lu Lab develops 2D/3D spatialtemporal omics, spatial pharmacology, and computational/AI approaches to map, model, and reprogram how cells
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(e.g., All of Us, UK Biobank, and Million Veteran Program), traditional cohorts (e.g., Women’s Health Initiative), and local Stanford data. Lab members have access to state-of-the-art computational
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to continue for a second year; any reappointment is contingent on satisfactory progress, program need, continued funding, and Stanford University approval. The appointment includes eligible medical, dental