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so in ways that invigorate practices of free expression in the university. Documentary or archival approaches are preferred, but we are open to all methods and humanistic fields of inquiry. All
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will contribute to developing and evaluating state-of-the-art methods for predicting mental health outcomes from multi-modal clinical and digital health data. This position offers the opportunity to work
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questions that lie at the interface of organic chemistry and chemical biology. The candidate will develop new chemical methods and small-molecule based probes to advance understanding of important biological
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new NIH-funded Center for Excellence in Multiscale Immune Systems Modeling. This position focuses on leveraging and developing new equation learning methods, such as Physics-Informed Neural Networks
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; Review methods manuals, scientific journals, and other literature for information applicable to research and write scholarly reviews of relevant literatures; Contribute to the preparation of grant
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, with a particular emphasis on Urban Resilience to Climate Risks. Current research themes include: • Adaptation of People: Leveraging big data and computational methods to analyze adaptation behaviors and
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Systems Modeling. This position focuses on leveraging and developing new equation learning methods, such as Physics-Informed Neural Networks (PINNs), Biologically Informed Neural Networks (BINNs), and
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quantitative methods and excited about discovering physical principles of biological organization. Minimum Requirements: PhD in a scientific disciplines, ideally Biology, Bioengineering, Physics or Math
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design and management; mentorship and coordination skills; familiarity with plant ecophysiology lab methods. Position details: • Start date: Flexible, as early as August 2026 • Location: Durham, North
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evaluation methods, discrete choice experiments, systematic reviews, and meta-analysis, with high levels of proficiency in associated software (e.g., Stata, R, Ngene). Applicants should have knowledge