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oxide catalysts for the oxygen evolution reaction The Laboratory of Energy Science and Engineering (LESE) headed by Prof. Müller (ETH Zürich, Department of Mechanical and Process Engineering) is looking
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PhD in Computational Materials Physics or a related area is required. Experience with electronic structure calculations is essential. Familiarity with the use of machine-learning tools in materials
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. 25 days of annual leave for fixed-term contracts. 1 day of Birthday Leave. Annual dental benefits. Committed to being a supportive employer as you prioritize your physical and mental wellness
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participate in the experiments, advise/guide for long-term knowhow transfer Publish the results in peer-reviewed journals and present at international conferences Your profile PhD degree in Physics or a related
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process conditions. Explore, adapt, refine, and validate analytical methodologies for FTIR, GC, and OES. Develop and propose original research ideas within the project’s framework. Interact closely with
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qualifications with a PhD in physics, electrical engineering, materials science or a related subject, and a background in magnetic thin films, nanostructures and spintronics. You should be motivated, proactive and
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(e.g., deep learning, explainable and physics-informed AI, large language models, etc.). The position will be developed within the funded project entitled “UrbanTwin: An urban digital twin for climate
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and validate the equipment. Your profile PhD in Materials Science, Mechanical Engineering, or Experimental Physics Experience in determining mechanical properties at surfaces Experience in surface
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experience of Python, VASP, PySCF, classical mechanics, scientific IT and data handling Experience in neural network architectures, bayesian optimization, random forest, kernel models, or gaussian process
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making new insights into landslide processes. You will develop advanced algorithms to process this data, with a focus on optical flow and object detection. You will interpret the results to better