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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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people’s livelihood; and the establishment of rule of law. Perform qualitative and/or quantitative analysis and use analyses to investigate mechanisms of authoritarian control and scenarios for transition
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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
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and multi-omics data analysis, and a high-performance computing environment (Unix/Linux) is highly preferred. An individual with Next generation sequencing experience is preferred. A good understanding
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measures combined with a standardized analytic pipeline applied consistently across studies, enabling biotype-based analyses and cross-project comparison. Supporting this program—and this position—are NIH