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gain experience in pooled screening techniques including library cloning, CRISPR screening, protein purification, proteomics and sequencing. We will use Python and Bash scripting to analyze and visualize
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for the identification, estimation, transportability, and generalization of the causal effects in complex real-world settings. Among others, methodological areas will span: ● Causal inference for spatiotemporal data
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been determined by school or unit leaders that some of the duties and responsibilities can be effectively performed at a non-Harvard location. The work schedule and location will be set by the department
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ability to use modern AI-assisted and agentic coding tools effectively, such as Claude Code, Codex, or similar systems, in research and development workflows. Ability to work effectively in a collaborative
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ability to use modern AI-assisted and agentic coding tools effectively, such as Claude Code, Codex, or similar systems, in research and development workflows. Experience in computational neurobiology
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inference pipelines for health effects and adaptation policy evaluation. Work with large, high-dimensional datasets (Medicare claims, census, weather, pollution, and related data), including data
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. Demonstrated ability to use modern AI-assisted and agentic coding tools effectively, such as Claude Code, Codex, or similar systems, in research and development workflows. Experience in computational biology
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approaches, and performing coarse-graining to obtain effective models at various scales. Special Instructions Contact Information Jason Eldridge https://www.physics.harvard.edu/ Harvard Physics Department 17