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power. Your primary tasks will be to: Develop a detailed 3D multiphysics model of the HT-PEMFC stack to analyze and optimize thermal management. Design a heat recovery system, tailored
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to capture vPvM chemicals in water. Optimize effect-directed analysis and implement suitable in vitro assays Investigate operational waterworks and if possible test pilot-scale systems such as advanced
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machine learning for safe and optimal control of cyber-physical systems. The projects are expected to be funded by the VILLUM INVESTIGATOR project S4OS (“Scalable analysis and synthesis of safe, secure and
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the Advanced Production Engineering (APE) research group that deals with the development, optimization and implementation of advanced production technologies and manufacture processes with emphasis on mechanical
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 19 hours ago
opportunities for career growth, skill development and lifelong learning and enjoy exclusive perks that include numerous retail and restaurant discounts, savings on local child care centers and special rates
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numerical modelling of natural clays at both laboratory and field scale. We are active members of the ALERT Geomaterials network and other international committees. Our diverse and international team of over
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on testing a set of promising pre-identified catalysts in the existing experimental set-up. Based on your findings, you will optimize the catalytic systems and/or adapt the experimental plant to achieve
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also recognizes the unequal capacities and risks involved, highlighting the “cruel” ascriptions to optimism and the potentially devastating consequences of aspiration. ASPIRA's approach identifying
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techniques that optimize both aspects. The candidate will perform the work together with a team of postdoctoral researchers who are experts on the field and other PhD student working in the topic. In general
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quantitative analysis skills and experience developing algorithms and/or conducting statistical analyses with biological datasets. Background and work knowledge in statistics, algorithms, optimization of novel