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to contribute to a collaborative, interdisciplinary research environment Are eager to learn and explore new ideas at the intersection of ML and optimization Can program efficiently in one or more languages
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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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for the efficient formation of high-value compounds. Advanced NMR methods and computational data analysis will be compounded to devise novel reactions towards pharmaceutical precursors, polymer building blocks and
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sunlight, air and water. Electrodes are a central component of the novel bioelectrochemical platforms for energy harvesting and microbial electrosynthesis. Optimal design of the 3D geometry and material
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academic partners in Europe and globally. Candidates with the following qualifications will be preferred: Educational background in power systems. Documented knowledge in optimization in power and energy
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. You will draw on ideas from Bayesian optimization and Bayesian deep learning, generative modelling, high throughput screening, and combinatorial synthetic chemistry. Responsibilities and qualifications
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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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for optimizing metals microstructures in-situ during the AM process as well as ex-situ during post-AM treatments and enable predictions of the microstructural evolution, and thus changes in properties, while AM
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for optimizing metals microstructures in-situ during the AM process as well as ex-situ during post-AM treatments and enable predictions of the microstructural evolution, and thus changes in properties, while AM
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on conventional computing platforms such as GPUs, CPUs and TPUs. As language models become essential tools in society, there is a critical need to optimize their inference for edge and embedded systems