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experimental systems neuroscience and excellent quantitative skills. Ideal candidates will have several years of practical experience performing neuro-behavioral and/or neuro-physiological experiments, including
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, molecular biology, and in vivo models. Analyze and interpret data, integrating experimental and computational findings. Utilize bioinformatics tools and techniques to analyze high-throughput sequencing data
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Health (HPH) (link is external) and Project Unleaded (link is external) for an exciting postdoctoral fellowship that contributes to a high-impact global program with a mission to create a healthier world
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Planetary Health (HPH) (link is external) and Project Unleaded (link is external) for an exciting postdoctoral fellowship that contributes to a high-impact global program with a mission to create a
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(100% FTE), 12-months/year, with an initial term appointment of ~4 years (48 months), renewable depending on funding and/or satisfactory performance. Start date The start date is negotiable and the
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optimization problems—often NP-hard and extremely difficult to solve at scale. These problems arise in diverse, high-impact domains, including renewable energy management, healthcare resource allocation, and
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Science. Proficiency in programming (Python, Julia), and high-performance computing (provide evidence with specific examples) Ability to work independently and collaboratively. Strong written and oral
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., diffusion transformers, multimodal representation learning) for modeling high-dimensional biological images. Develop computational methods to reconstruct and simulate 3D tissue architecture and dynamics
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research in ML for Health, including HIPAA-compliant compute infrastructure with high memory GPUs and access to Stanford Healthcare data, which includes EHRs for over 5M patients and 100M clinical notes
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learning to derive principled models of cortical computation. Our newly refurbished primate facility, state‑of‑the‑art Neuropixels rigs, and high‑performance computing cluster offer an unmatched playground