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U.S. Department of Energy (DOE) | Washington, District of Columbia | United States | about 3 hours ago
funded technologies and processes to optimize synthetic fuel production in remote/austere locations Assessment of critical mineral supply chains for opportunity to optimize for cost, energy, and production
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for someone who loves to solve complex physical problems, is passionate about mathematics and enjoys programming, and wants to see their work directly influence product development from the ground up. This role
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, reinforcement learning, multi-objective optimization (mathematical programming, heuristics/meta-heuristics). Proven success as PI/co-PI or primary writer on large proposals (e.g., NSF/DOE/DoD/state/industry), and
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13 Dec 2025 Job Information Organisation/Company Uppsala universitet Department Uppsala University, Department of Information Technology Research Field Chemistry Computer science Mathematics Physics
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Infrastructure? No Offer Description - main mission: The team is based at the Laboratory of Pathogens and Host Immunity (LPHI) at the University of Montpellier and focuses on applying mathematical and
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models to the design of sustainable processes in chemical engineering. To bridge the scale from molecules to processes, we apply state-of-the art mathematical concepts and tools combined with highly
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established, optimized, and maintained over time. Key tasks Design, construct, and maintain synthetic microbial consortia composed of cyanobacteria and actinomycetes for sustainable bioproduction Investigate
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, optimization, statistics/data ethics, etc.). Develop or expand curriculum offerings in data science and/or applied mathematics. Maintain an active research program, ideally involving undergraduate student
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-ever Immune Digital Twin – a personalizable computer replica of the immune system – to enable everyone and anyone to assess and optimize the health of their immune system and simulate and predict its
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therapeutics by protein design. This project will apply cutting-edge generative AI methods—including protein design, structure–function prediction, and multimodal learning—to develop and optimize a new