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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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Dr. Bridgett vonHoldt is seeking to hire a postdoctoral associate (or other senior research) in the areas of evolutionary and ecological analyses of large genome datasets, modelling and simulation
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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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required) Kinetic modeling proficiency (Chemkin, Cantera), analytical proficiency (sensitivity, rate of production, etc.) Spectroscopic modeling experience preferred (HITRAN/HITEMP) Familiarity with
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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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background in chemical and biological engineering, bio-engineering, molecular biology, microbiology, biochemistry, biophysics, computational modeling or related fields. Experience in metabolic engineering
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communication skills Expertise in Generative AI: Strong background in machine learning, with specific experience in Large Language Models (LLMs), and Vision-Language Models (VLMs) Excellent programming skills
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
to develop hybrid models for sea ice that combine coupled climate models and machine learning. Our previous work has demonstrated that neural networks can skillfully predict sea ice data assimilation
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large AI models or their applications. Current PLI projects involve work with language, images, multimodal data, science/math, code, and scientific data. PLI is also focused on AI safety, fairness, and