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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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/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 Silvio O
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) with expertise and interest in Large Language Models (LLM) for Energy Environmental Research and Applications. The researcher(s) will work with the principal investigator and team to develop, fine tune
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advance regenerative medicine. For more information about the lab, please visit https://mesa-lab.org/ .Projects will utilize in vivo mouse models, transcriptomic techniques, and advanced intravital imaging
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about each Principal InvestigatorRabinowitz, Joshua - Major areas of interest include: Metabolomics, isotope tracing, metabolic flux analysis, quantitative modeling, mass spectrometry imaging, cancer
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), multi-level modeling, and experimental study design. Expertise designing studies with parents, infants, and school-aged children is particularly desirable. The Postdoctoral Research Associate will work
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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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data analysis (e.g., RI-CLPM, growth-curve analysis), multi-level modeling, and experimental study design. Expertise designing studies with parents, infants, and school-aged children is particularly
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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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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