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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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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
: 271598471 Position: Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning Description: The Atmospheric and Oceanic Sciences Program at Princeton University, in
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The Skinnider Lab at Princeton University aims to recruit a postdoctoral fellow or more senior researcher to work on projects related to computational analysis of chemical and biochemical datasets
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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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access to state-of-the-art numerical models and high-performance computing systems at Princeton and in NOAA, working alongside GFDL model developers and software engineers to advance quality assurance and
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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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or acquire further expertise in quantitative intravital microscopy. 2) Computational or Cell biologists (with expertise in quantitative microscopy, statistical modeling, cell culture, and/or biochemistry
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preprocessing and curation in addition to model development and evaluation. This opportunity will prepare candidates for a range of competitive positions in academia or industry that involve computational biology
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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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maintaining a shock tube facility (operational proficiency required)Kinetic modeling proficiency (Chemkin, Cantera), analytical proficiency (sensitivity, rate of production, etc.)Spectroscopic modeling