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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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) 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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ionics, materials characterization and/or electrochemical engineering. We seek candidates with an interest in participating in large multi-PI grants and with collaborative research experiences, experience
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or more of the following: software package development and maintenance in R; record linkage/entity resolution; data privacy techniques; large data processing and high performance computing; advanced causal
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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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. A major focus will be on the identification of small molecules from mass spectrometry-based metabolomics data, in part based on generative AI models of chemical structures. The position is available
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emerging technologies such as artificial intelligence, quantum technologies, and space-based systems, including large satellite constellations. A recent PhD in physics, engineering, computer
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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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activities such as working with large, longitudinal datasets, designing and implementing lab-based experiments, coding video data, writing manuscripts, presenting research, and mentoring undergraduate and
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package development and maintenance in R; record linkage/entity resolution; data privacy techniques; large data processing and high performance computing; advanced causal inference and statistics; computer