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multidisciplinary research in energy markets, optimization, game theory, and machine learning. Our team of 13 members (link ), from 10 different nationalities, values diversity and includes experts from a range of
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and research, in and outside academia. About the project The proposed research aims to optimize the design of timber building systems with innovative connections and achieve an extended service-life
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underground conditions. Apply machine learning and AI techniques to enhance model accuracy and optimize design parameters. Contribute to the development of a comprehensive, AI-based design methodology for LUS
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criteria Demonstrated knowledge and experience in electrical system modeling and analysis, applied control, power electronic systems, optimization techniques, and/or machine learning. Experience with
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. The position will work with the Technical Directors of Quantum Infrastructure and the Petersen Institute for Nanotechnology, the faculty, and the electronics and machine shops to design and optimize new and
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well as on how different user groups experience and utilize these solutions. Are optimal solutions being chosen today? Are the solutions being used as expected by the user groups they are intended to serve? Is the
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partner in an exciting 5-year collaborative program. We are currently seeking applicants for three PhD projects as listed below. The successful candidates will be based in either NIBRT or UCD and will also
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drive the gradual development of these technologies toward real-world applications. This involves engineering experimental hardware for cell culturing workflows, optimizing experimental processes, and