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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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-microenvironment interactions during cancer progression. Ludwig Princeton Branch is dedicated to accelerating the study of metabolic phenomena associated with cancer to develop new paradigms for cancer prevention
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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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Science and Engineering, or a related area is required. The position will involve developing models and algorithms for the evolution of inorganic aerosols in the atmosphere, building upon the research
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and society, is developing an emerging research and teaching program in design that embraces Princeton's commitment to the betterment of humanity through deliberative, informed, and thoughtful design
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research positions in the following fields:1. Microfluidic and Lab-on-Chip development in a multidisciplinary lab. Candidates should demonstrate track-records in microfluidics, Lab-on-Chip, and micro
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) for Energy & Environmental Research and Applications. The researcher(s) will work with the principal investigator and team to develop, fine tune, and deploy LLM based tools for environmental engineering
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position to work on a new collaborative project in a team with expertise in plasma and plasma-surface interactions, surface science, and quantum metrology. The overall goal of the project is to develop
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
association with NOAA's Geophysical Fluid Dynamics Laboratory (GFDL), seeks a postdoctoral or more senior research scientist to develop hybrid models for sea ice that combine coupled climate models and machine
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courses. Program faculty and senior researchers will offer mentoring to support professional development. Former postdoctoral researchers with SGS have pursued careers in academia, nongovernmental and