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. The objective is to further develop and validate machine-learning surrogate models derived from high-fidelity multiphysics simulations of reactor transients and quantify how surrogate uncertainties propagate
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, computationally expensive, model simulations. This experimental design process is envisioned to update iteratively as new data become available to optimally infer surface fluxes across the landscape. The work will
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approaches, generalized linear mixed modeling, and performing simulations using specialized statistical programming tools. Writing and publishing papers in international, peer-reviewed journals. An important
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modifications of the biomolecular landscape of bacterial cells contribute to bacterial physiology, pathogenesis and drug susceptibility, iii) understanding and modelling pathogenesis and treatment failure
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the offer, initially planned for November 2026. The PhD candidate is expected to participate in simulation and experimental activities related to autonomous spacecraft systems and validation frameworks
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and drug susceptibility, iii) understanding and modelling pathogenesis and treatment failure of difficult-to-treat clinical infections. The main model organisms used in our team are Staphylococcus
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and targeted, computationally expensive, model simulations. This experimental design process is envisioned to update iteratively as new data become available to optimally infer surface fluxes across
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is connected to the field of innovation studies with a specific focus on sustainability transitions, circular economy, business model change and value chains related to electric vehicle (EV) batteries
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. The successful candidate will contribute to the development of experimental model systems for studying metabolite exchange, microbial community interactions, and engineered microbial consortia in marine
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shipping, identify critical criteria for integration and operation, and develop a model for simulation of the energy system. This includes normal operations, ramping, transit vs. port stay, and maintenance