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of the lab to design and perform experiments with a particular focus on immunometabolic pathways in vitro and in vivo including analysis of mouse model of obesity and cancer. This is a one-year appointment
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skills with the ability to learn new computer skills including word processing, spreadsheets, databases, and PI archive database Exposed to heat, noise, dust, and hazardous areas around machinery
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optimization and meta-heuristics; economic paradigms (game theory, mechanism design, electronic markets); agent modeling and simulation; agent planning, scheduling and decision support; agent learning and
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experience in manufacturing systems modeling, simulation (i.e., DES), and digital twins. • Good knowledge and experience in machine learning, reinforcement learning, and AI-based optimization for production
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working 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
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genome-resolved multi-Omics methods, statistical/metabolic modeling, and machine learning. The postdoc will apply these approaches to generate a systems-level understanding of microbiomes including
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Engineering, or related field. Research experience with Artificial Intelligence/Machine Learning/Large Language Model. Publication track record in a series of top tier conference papers e..g, in NeuRIPS, ICLR
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. This PhD will focus on uncertainty-aware machine learning models, developing and evaluating techniques (e.g., Bayesian and interval neural networks) to quantify model uncertainty and monitor it during
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systems at various scales, for example using ab initio electronic structure methods like density-functional theory, developing interatomic potentials with various methodologies including machine learning
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mathematical modeling and programming. * Research experience and publications in machine learning, complex networks, and mathematical modeling. * Excellent English communication skills (written and oral