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research project You will be involved in metabolic and physiological studies to address metabolic organ communication in a cardiorenal-metabolic project. You will work with mouse models of human disease and
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engineering parts. This position offers a unique opportunity to drive the development of system-level digital-twin and optimization methodologies—integrating electrolyzer models with renewable generation, power
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understanding of statistical modelling is required to match the research at different scales from individual laboratory experiments to large-scale long-term studies. Methodologies that the statistician is
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Professor for the Section for Thermal Engineering who can strengthen and further develop our activities within electronics cooling, thermal-fluid modelling, and the integration of thermal design
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Professor Aldo Faisal from Imperial College London involved as international project partner. Research objectives and tasks You will contribute to the development and empirical validation of models
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-Physical Energy Systems The PhD position focuses on the development of secure and trustworthy AI for resource-constrained embedded systems. The research will investigate how machine learning models can be
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textiles. The projects are carried out in close collaboration with industrial and societal partners and aim to develop, test, and implement innovative circular concepts and business models that reduce
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focuses on the development of secure and trustworthy AI for resource-constrained embedded systems. The research will investigate how machine learning models can be designed and deployed efficiently
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, visualizing data, and writing clean & reproducible code) Experience with natural language processing tasks (in R or Python - familiarity with common tasks such as sentiment analysis, topic modelling
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Engineering. The position is closely connected to our activities within developing high-fidelity models that capture the coupled thermal, chemical and electrochemical phenomena governing system performance