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learning, or related quantitative field. • Proficiency with deep learning frameworks (e.g., PyTorch, TensorFlow, and JAX). • Experience in PDE/ODE modeling and numerical methods. • Strong interest in
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deep learning frameworks (e.g., PyTorch, TensorFlow, and JAX). • Experience in PDE/ODE modeling and numerical methods. • Strong interest in interpretable ML and mechanistic model discovery. Submit a
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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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, 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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. Occupational Summary The David Lab at Duke University (www.ladlab.org ) is recruiting a postdoctoral fellow to join an established research group developing and applying DNA sequencing and computational
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conventional methods like nonlinear FEM, and comparing the results to computational observations. 3) Support the educational activities of the Pl through graduate student mentoring, selected lectures, 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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; (ii) an impact evaluation of a large-scale tree-growing program in Kenya, Tanzania, Uganda, and India; and (iii) an analysis of financial incentives for smallholder tree growing in Ethiopia. In
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. Minimum Requirements: PhD or equivalent doctorate (e.g., ScD, MD, DVM) in psychology, psychiatry, neuroscience, biostatistics, bioinformatics, computer science, or a related field. Research background in
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. The appointment is not part of a clinical training program, unless research training under the supervision of a senior mentor is the primary purpose of the appointment. The Postdoctoral Appointee functions under