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in physics, chemistry, material science, industrial ecology, or a related discipline Expertise in one of the following areas: Life cycle assessment, material supply evaluation or circularity of PV
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. The data acquired with your chip(s) will be analyzed with machine-learning algorithms. You will collaborate with researchers and companies of various disciplines like chemistry, embedded systems, software
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Physics, Materials Science, Chemistry, or related field. Strong background in computational materials science, with DFT simulation expertise. Experience with DFT software (e.g., VASP, AMS, Quantum ATK
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, kinetics and in situ/operando methodologies. The ideal candidate: has a PhD or draft PhD thesis in chemistry and/or chemical engineering is a highly motivated and an enthusiastic researcher, with a keen
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draft PhD thesis in chemistry, chemical engineering, material science, and/or related area. is a highly motivated and an enthusiastic researcher, with a keen interest in catalysis. Experience with