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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 starting July 2025, and will remain open
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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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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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of laminar/neuropixel probes and electrical microstimulation to study attention and decision making networks in a behaving animal model together with parallel studies in humans. The project is part of a NIMH
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information about the lab, please visit https://mesa-lab.org/. Projects will utilize in vivo mouse models, transcriptomic techniques, and advanced intravital imaging to investigate: 1) How immune cells localize
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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
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discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials. Candidates who are nearing completion
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on developing new systems models to examine social and biological drivers of infection inequality. The overarching goal of this postdoctoral position is to advance the use of mathematical and statistical models
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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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, lipid vesicles, polymer physics, active materials, single molecule biophysics, biomaterials, materials chemistry, fluid mechanics, rheology, and computational modeling. Candidates should apply at https