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OPTIMIZATION FOR COMPLEX ENERGY AND SUSTAINABILITY PROCESSES Are you looking for a future industrial research position or a long-term academic career? Do you want to be part of building up research – preferably
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Salford Business School is seeking a talented and motivated Postdoctoral Research Fellow to join our interdisciplinary research team working at the forefront of sustainable energy systems. This is an exciting opportunity to contribute to a high-impact project focused on flexibility modelling and...
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School of Engineering invites applications for Doctoral Researcher in Sustainable Renewable Energy Engineering, Modeling and Optimization Department of Energy and Mechanical Engineering is a community of
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collaboration with IHL and an industry partner. where you will be part of the research team to develop and demonstrate Building-to-Grid Integration through Intelligent Optimization and Predictive Control at SIT’s
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experimental analysis of optoelectronic properties. We will deploy a cutting-edge combinatorial approach, correlating atomic-scale resolution imaging and multiscale defect mapping approaches with macroscopic
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experimental analysis of optoelectronic properties. We will deploy a cutting-edge combinatorial approach, correlating atomic-scale resolution imaging and multiscale defect mapping approaches with macroscopic
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an excellent publication record. Solid research experience in one or more of the following topics is expected: Graph neural networks Optimization algorithms Predicting structured output Self-supervised learning
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in the development, validation, and optimization of 3D-printed Ship Hull and Connector System. This includes conducting finite element modeling, ship resistance and stability assessments, as
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parameter, representing the elementary act of writing a bit of information. As THz photons exactly match the excitation energy, this represents the optimally energy efficient switching regime, avoiding
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processors. The candidates will contribute to topics including: The offline and online calibration of learning systems through methods such as conformal prediction, hyperparameter optimization, and reliable