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optimization sub-group of the Reliability and Risk Engineering Lab. To this aim, the successful candidate will: Advance mathematical optimization methods to further our understanding of future energy systems
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be carried out in collaboration with groups in theoretical chemistry, computer science and applied mathematics. Job description As a PhD student in our growing team, you will perform quantum-chemical
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, engineering, or computer science You have a PhD in computational neuroscience, physics, data science, or mathematics You have the required social and leadership competencies that allow you to prosper at ETH
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100%, Zurich, fixed-term The professorship for history and philosophy of mathematical sciences , led by Prof. Roy Wagner, is a place for reflecting on all aspects of mathematical knowledge from
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, computer science, or related fields. This includes, but is not limited to, psychology, mathematics, engineering, physics, or statistics. Geographical Eligibility: We are seeking candidates who are currently
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field, such as Chemistry, Physics, Engineering or similar Have an excellent track record and meet the general admission requirements for a doctorate at ETH Zurich Previous experience in solid-state NMR is
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Earth Sciences / Physics / Mathematics / Computer Sciences or a related discipline is required. Applicants must have obtained their Master's degree by September 2024 A strong foundation in analyzing large
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learning, deep learning, and topological optimization. Highly motivated, self-driven, and shows excellent performance Strong analytical, mathematical, and algorithmic capabilities Understanding and
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100%, Zurich, fixed-term The Chair of Energy Systems Analysis (ESA), within the Department of Mechanical and Process Engineering at ETH Zurich, is looking for a highly motivated Post-Doctoral
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science, statistics, applied mathematics, or related fields Proficiency in developing and deploying machine learning models (e.g., using Python, R) Experience in data wrangling and feature engineering