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vulnerability modeling, and (c) population and built environment exposure to climate hazards. The broad agenda of this research is assessing the fitness of geospatial indicators to inform conceptual and policy
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The Princeton University WET LAB (https://ren.princeton.edu/) is seeking a postdoctoral research associate(s) or more senior researcher(s) with expertise and interest in Large Language Models (LLM
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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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earth system model data, with an emphasis on Seamless System for Prediction and EArth System Research (SPEAR) for seasonal to multidecadal prediction and projection. The project will emphasize elements
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, to study novel renewable energy technologies. The candidates are expected to have a PhD degree in Chemical Engineering or related field, and have experience with optimization (theory, modeling, and tools
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optimization (theory, modeling, and tools). Candidates should apply at: https://www.princeton.edu/acad-positions/position/39361 and include a cover letter, CV (including a list of publications), research
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. A major focus will be on the identification of small molecules from mass spectrometry-based metabolomics data, in part based on generative AI models of chemical structures. The position is available
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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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researchers working on an NIH funded project focused on developing new systems models to examine social and biological drivers of infection inequality. The overarching goal of this postdoctoral position is to
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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