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Field
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numerical optimization and simulation models. Proficiency in one of the major programming languages such as Python A collaborative team player with a desire to make a personal impact within our
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well as surface and bond properties Determination of sorption properties of An-MOFs towards fission products Development of novel An-MOFs with optimized sorption properties Presentation of the results in scientific
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reactor, with the goal of designing an optimized reactor for direct C2H4 production. Your colleagues: As a PhD Candidate, you will work in the plasmalab team in the Faculty of Science and Engineering
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of transverse transport on heat and mass transfer in a thermal arc plasma reactor, with the goal of designing an optimized reactor for direct C2H4 production. Your colleagues: As a PhD Candidate, you
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, ranging from soft matter to biology to synthetic chemistry. The laboratory benefits from numerous academic and industrial partnerships in France and worldwide. Its openness, recognition, and state
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nano-scale objects Designing and building a coherent low-energy electron microscope Sample preparation and recording holograms Numerical reconstruction of the sample structure Presenting the results
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require efficient numerical algorithms to be practical and to enable robust optimization. Therefore, in this project you will: Develop efficient numerical methods and strategies to solve the electromagnetic
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electrolysis and fuel cells (SOEC and SOFC). By combining numerical modeling with data-driven approaches, you will identify optimized operating conditions and strategies to improve both steady-state and dynamic
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linkages based on numerical simulations and to transform them into AI- and ML-ready information to develop and implement an indirect inverse optimization framework to identify microstructures that exhibit
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and designing sustainable P2X value chains. As a PhD researcher, you will contribute to the new stack designs for high-temperature electrolysis and fuel cells (SOEC and SOFC). By combining numerical