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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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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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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. Conte Center on the "Cognitive Thalamus". The successful
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systems at Princeton and in NOAA, working alongside GFDL model developers and software engineers to advance quality assurance and data dissemination capabilities for making high-resolution earth system
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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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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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health services to Princeton University faculty, staff, and employees. An integrated, evidence-informed model guides all UHS practices and services. UHS leverages clinical encounters and prevention efforts
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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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, 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