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on diverse scientific and security problems of interest to BNL and the Department of Energy (DOE). Topics of particular interest include: (i) development of novel machine learning models and adaptation
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investigators. Position Requirements Ph. D. in theoretical or physical chemistry, or a related field Extensive experience in one or more of the following areas: Computational modeling of homogeneous
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for the characterization. Prepare research based manuscripts for publication Participate in the meetings related to the EFRC Required Knowledge, Skills, and Abilities: PhD in Condensed Matter Physics, Materials Science
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novel genetic pathways regulating local and systemic acquired resistance, as well as growth-defense trade-offs. Using bacterial, fungal, and viral disease models, the research will focus on identifying
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scientific and security problems of interest to BNL and the Department of Energy (DOE). Topics of particular interest include: (i) novel development of deep learning ML models and adaptation of existing ones
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life – including the explosion of large language model (LLM) releases. BNL is engaged in numerous research efforts that employ NLP techniques for science and security applications and uses
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subject to renewal contingent on performance and funding. BNL policy requires that after obtaining a PhD, eligible candidates for research associate appointments may not exceed a combined total of 5 years
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of relevant work experience as a post-doc and/or in an R&D position, excluding time associated with family planning, military service, illness or other life-changing events. Candidates must havereceived a PhD
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industry, education, and public life – including the explosion of large language models (LLMs). BNL is engaged in numerous research efforts that employ NLP techniques for science and security applications
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-loss-spectroscopy is highly desirable. - Demonstrated quantitative data analysis abilities. - Effective communication skills. BNL policy requires that after obtaining a PhD, eligible candidates for