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models that integrate data from quantum simulations and experiments, using techniques such as equivariant graph neural networks with tensor embeddings. We aim to train these methods in a closed-loop
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data Design algorithms for correlating low-level events into process-level attack models Contribute to joint framework development with TU/e on continual learning Collaborate with industry partners
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Senior Researcher in Synthetic Biology and Metabolic Engineering of power-to-X utilizing Microorg...
. We are seeking a Senior Researcher to lead pioneering work in synthetic biology and metabolic engineering, with a particular focus on non-model prokaryotic microorganisms capable of utilizing power
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to circularity and sustainability in the footwear industry. Through advanced experimental work and modeling, you will help uncover how the composition of shoes will affect the circularity potential, and advice
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of the Marie Skłodowska-Curie Doctoral Network SCARPA, a European training network committed to circularity and sustainability in the footwear industry. Through advanced experimental work and modeling
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. Work will also involve electrochemical modelling using existing models and using AI based tools. The focus of the work will be to cater to the needs to high voltage/power in power electronic systems
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cement based on literature, theory, and experiments. Optimization of composition with other waste materials. Thermodynamic modelling and experiments with advanced technologies are used. Development of a
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and colleagues working with theory that will complement your work with density functional theory, phase-field simulations, and finite element modelling. Qualified applicants must have: Enthusiasm
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Analytics. The core focus of the PhD project will be to develop and test planning and optimization models to analyze new and innovative Hospital-at-Home systems to improve access to healthcare for elderly and
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and operation of building HVAC systems, these technologies support both energy efficiency and flexible demand objectives. Model predictive control (MPC), which involves physics-based building energy