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, processor/system simulators (Gem5, NVSim), SystemC, HLS tools, abstractions and intermediate representations, Programming models, MLIR, LLVM, experience in code optimization, programming expertise in C, C
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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The group ofSebastian Stich works on the design and analysis of optimization methods
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optimization lab (EES EMPDO lab). The former focuses on intelligent energy network research, including: demand management and flexibility, digital twinning, data analytics, smart grid ICT architectures and
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or crinkled. The PhD student will investigate different biomimetic materials and explore how to build membranes with complicated morphologies that will deliver optimal performance in devices. The project will
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: Digital twin and process optimization with AI Where to apply E-mail doctorats.industrials.recerca@gencat.cat Requirements Research FieldMathematicsEducation LevelMaster Degree or equivalent Research
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | about 1 month ago
close collaboration at all stages of a research project exploring applications of deep learning and artificial intelligence to dynamic portfolio optimization problems. This position offers the opportunity
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the evaluation, the intensification and the optimization of carbonation (biotic and abiotic) processes involving different feedstocks, to address three different applications of industry decarbonation, in straight
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for the CERIC-ERIC project “LEMIS” aiming to adopt and improve existing Ion Beam Analysis (IBA) techniques for their optimal use in the analysis of materials of importance to energy storage. The successful
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. This research is performed in two research labs: the Digital power and energy systems lab (EES DigiPES lab) and the Electricity markets and power system optimization lab (EES EMPDO lab). The former focuses
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for food, feed, and fiber handling and storage. Apply mathematical modeling and scientific principles to optimize operational performance. Collaborate with faculty, graduate students, and industry partners