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, doing 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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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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, 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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learning, or related quantitative methods preferred but not required. Be Bold. Position Description: Engage in substantially full-time research or scholarship under the guidance of a faculty mentor, focusing
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animal species, generating standardized data that works effectively across diverse languages and cultural contexts while eliminating traditional barriers of recall bias. These methods are being deployed in
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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