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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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project studying the neurocomputational basis of reinforcement learning in rodents. The project, in collaboration with the Berke and Frank labs at UCSF, combines advanced system neuroscience and
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are interested in candidates who have an interest in: *Advanced Manufacturing and Integration of Scalable Structures *Soft and Living Materials *Natural and Engineered Materials for Energy, Environment and
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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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The Princeton University WET LAB (https://ren.princeton.edu/) is seeking a postdoctoral research associate(s) or more senior researcher(s) with expertise and interest in Large Language Models (LLM
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Plasma Physics Lab and in the Physics, Geosciences, and Mechanical and Aerospace Engineering Departments, and at the nearby Institute for Advanced Study. The expected start date is September 1, 2026
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cognitive neuroscience, and houses state of the art facilities for experimental research in all of these areas, as well as advanced computational resources that support theoretical and quantitative approaches
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revolutionize the understanding and advancement of human health by conducting interdisciplinary foundational research, developing and harnessing advanced computational approaches, and training the next generation
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, to study novel renewable energy technologies. The candidates are expected to have a PhD degree in Chemical Engineering or related field, and have experience with optimization (theory, modeling, and tools
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, including but not limited to cement chemistry, material science, or structural materials and mechanics. Candidates with a strong commitment to interdisciplinary research are especially encouraged to apply