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application! Work assignments The Division of Automatic Control at the Department of Electrical Engineering invites applications for a postdoctoral position in optimal motion planning and model predictive
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or reconstruct the missing links. The first step is to explore different optimization methods using low rank tensor minimization and tensor decompositions paired with auxiliary information in order to recover
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design theory that facilitates multi-objective, multi-disciplinary optimization of data center design considering location, building operations, materials, energy use, water use, cooling system design, and
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 12 hours ago
design theory that facilitates multi-objective, multi-disciplinary optimization of data center design considering location, building operations, materials, energy use, water use, cooling system design, and
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the development of high-reliability fiber components and optimized doped fibers. The first objective of this project is to explore different approaches to develop fluoride fiber components and build optical benches
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applications for a Postdoctoral Researcher position. The selected candidate will undertake both collaborative and self-directed research on mathematical modeling, optimization and simulation models/algorithms
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Materials has diverse research activity, focusing on different aspects of material and energy related questions. We contribute to a sustainable society by developing improvements for materials and energy
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of these two postdoc positions is to contribute to the modelling, simulation, and optimization across different LDES technologies, from device (ESS+inverter) to system level (grid integration) under different
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private - and stakeholders in the different fields of research. We look forward to receiving your application. Join us and build the future with us! Read more about our benefits and what it is like to work
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between growth and defense by evolving different strategies to optimize interactions with their microbial environments to maximize fitness. Our long-term goal is to investigate fundamental mechanisms