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, lipid vesicles, polymer physics, active materials, single molecule biophysics, biomaterials, materials chemistry, fluid mechanics, rheology, and computational modeling. Candidates should apply at https
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cells (i.e., formation of biomolecular condensates) and to leverage these findings for bioengineering applications. Candidates completing (i.e., with a confirmed defense/viva date) or holding a PhD in
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, combines advanced system neuroscience and computational modeling techniques to study planning in rodents engaged in dynamic spatial foraging tasks. The successful candidate will develop computational models
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model output available to a diverse audience. Candidates must have a PhD in computer science, environmental and physical sciences, or a closely related field. The following attributes are desirable: a
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implementation of experiments for a DARPA-funded project starting in July 2025. This position offers the opportunity to gain research skills in bioengineering and perform team-based research on a fast-paced
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genome-scale datasets, as well as proved expertise in their curation and analysis using state-of-the-art phylogenetics implementing phylodynamic models. Strong computational skills and programming
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incident angles for benchmarking and validation of theoretical calculations and computational physics and chemistry modeling of important surface processes occurring at plasma-material interfaces in fusion
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interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials
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, single molecule biophysics, biomaterials, materials chemistry, fluid mechanics, rheology, and computational modeling. Candidates should apply at https://puwebp.princeton.edu/AcadHire/position/38901 and
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University to merge CFPS data with granular COVID mitigation policy data and specify models for evaluation of policy effects. *Communicate with the director of the secure data enclave at Peking