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-class research program in cell biology, studying fundamental principles underlying the organization and function of cells and tissues. Researchers utilizing invertebrate and non-traditional models
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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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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
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mathematics, data science and learning, high-performance computing, multiscale integrated modeling, and software technology. While our current strengths reflect the traditional focus of the Laboratory
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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
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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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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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science and learning, high-performance computing, multiscale integrated modeling, and software technology. While our current strengths reflect the traditional focus of the Laboratory on magnetic confinement
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interpret statistical or computational research, and follow developments in the fast-changing field of AI, including but not limited to, familiarity and technical understanding of AI models and their uses and
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debt capacity model. Produce management reports (both financial and graphic) to convey the status of the debt program and to support recommendations. Represent the needs of the department to both