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the interview process. Mentorship Structure The postdoctoral fellow will be supervised by Prof. Sarah Fletcher and will collaborate with other members of the lab. Mentorship of the postdoctoral fellow will be
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an ambitious and motivated postdoctoral scholar to join an exciting project focused on a unique alignment of visual, acoustic, and structural data for a radical new assessment of anthropogenic impact on our
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learning, expanding our lab’s core strengths in behavioral and computational approaches to studying social cognitive development. Mentorship Structure The postdoctoral fellow will be mentored by Professor
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groups. The fellow will also help with grant writing to get practiced in the skill of academic fundraising that will be vital for their future career. Mentorship Structure The postdoc will be a member of
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employ advanced analytical methods in large databases, which include claims data and electronic health record data in conventional structures and in common data models. Our research group prioritizes a
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digestion), and should have documented capabilities using a variety of simulation and optimization techniques. Familiarity with electric power grids and rate structures is highly valued, as is experience with
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study of ECE and policy impacts. Strong data analytical skills using advanced statistical methods (such as mixed effect models, multilevel modeling, structural equation models, longitudinal modeling, etc
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outcomes of a priority project, while also contributing to secondary efforts. Responsibilities include gaining deep familiarity with study assessments, protocols, data structures, and—where applicable
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community at Stanford looking at the health impacts of environmental changes. The successful candidate will have strong data skills, including experience handling complex data structures, working with spatial
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. This includes integrating LLMs with structured data sources to develop robust computational phenotyping algorithms and scalable models for real-world evidence generation. The role will involve both method