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and ground), and boasts expertise in controlling and deploying them in practice, as well as in designing coordination strategies for them. Our recent work on ML-based co-optimization demonstrates some
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modelling framework that can serve as a digital twin of the manufacturing process allowing for a faster and more precise optimization trough virtual engineering.You will work within a research team comprising
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- and Q-band EPR spectrometer. The candidate will be responsible for designing, building, and optimizing instrumentation and methods to investigate complex catalytic systems — including both synthetic and
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electromagnetic simulation techniques and incorporate the characteristics of new materials to design motor structures, and perform multi-objective optimization aimed at enhancing motor efficiency, power density
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optimize the impacts of food production, processing and consumption on both the environment and nutritional health, combining nutritional and health sciences with life cycle assessment and absolute
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Implementation, further development and adaptation of AI models and research prototypes for the annotation and scoring of text data, in particular for the optimization of AI-supported teaching and learning in
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Applications are invited for a position in the rapidly expanding data analytics run by Prof Adam Dubis. The main focus of the team is to develop deep learning tools for prediction of disease progression
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Regular Job Code 9742R5 Employee Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job Required Qualifications: * Ph.D. or Masters with equivalent experience in Computational
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disciplines). Experience in/Dedication to: planning and conducting chemical experiments, chemical analysis, process modeling/simulation, and optimization Team player skills and enthusiasm to work in a multi