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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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simulations, statistical mechanics, computer programming (e.g., C++, Python), polymer theory, molecular modeling (e.g., of proteins, nucleic acids, ligands), coarse-grain and polymer model development
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AI models (especially language models); (b) Applications of large AI models to many academic disciplines; and (c) Studying the impact of large AI models on society and the world. The Initiative will
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Models of Human Cognitive Function," and potentially seed projects supported by NAM. Candidates can read more about these core projects and funded seed projects at https://nam.ai.princeton.edu/research. In
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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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responsibility for project success, through a variety of means such as training, mentoring, and coaching. Serve as role model for the PM and project team through making timely and supportive decisions. Closely
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. Initiate and maintain open collaboration with researchers across Princeton University. Regularly meet with, listen to, and ask questions of researchers to ensure the engineered solutions fit the research
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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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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