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Medicine are seeking to appoint a Postdoctoral Research Fellow to join a project developing and validating deep learning computer vision models to classify mosquito breeding habitat on very high-resolution
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computational biology and bioinformatics and have made discoveries that are opening the door to possible new treatment approaches to diseases without therapies as well as ways to improve medical care using
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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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of innovation in pain research, education, and patient care. Our postdoctoral program has successfully transitioned fellows into independent research careers; many have achieved their own NIH K/R grants and
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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