61 proof-checking-postdoc-computer-science-logic Postdoctoral positions at Technical University of Munich
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                23.07.2025, Wissenschaftliches Personal The Ecosystem Dynamics Group at the TUM School of Life Sciences, Technical University of Munich studies how ecosystems change in time and space. We quantify 
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                the faculties of medicine and computer science at TUM, as well as the Munich Center for Machine Learning (MCML). It is a great place for interdisciplinary research between medicine and data science. We 
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                14.12.2022, Wissenschaftliches Personal The BMBF-funded position is part of the CoMPS project, which is a multidisciplinary project combining the fields of mathematics, computer science, geophysics 
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                advanced wet-lab experience in molecular biology and in reverse genetic approaches. • You are familiar with FAIR data handling and in silico data analysis. • You work precisely and reliable. YOU FIT TO US 
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                zusammen mit insgesamt elf Postdoc WissenschaftlerInnen aktiv am wissenschaftlich-akademischen Diskurs zur aktuellen Forschungs- und Entwicklungsfragen im Bereich des Grünen Wasserstoffs teilnehmen. Von 
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                engineering, computer science or electrical engineering, with good grades. Experience in scientific work, project proposal writing and team leadership are part of your repertoire. In addition, you are 
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                . Your qualifications An excellent PhD degree either in Computer Science, Physics, Mathematics or related fields, ideally with a background in quantum theory, quantum computing or quantum machine learning 
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                mathematics, computer science, information technology, electrical engineering, physics, mechanical engineering, or a comparable qualification Sound knowledge of mathematics and physics, especially in the fields 
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                , computer science, mathematics, physics, or a related field with an outstanding academic record. Interest in mathematical signal processing, optimization, and/or machine learning is important. Since 
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                PhD degree in biology, physics or a related discipline. You have experience in quantitative biology, experimental soft matter, or experimental biophysics. You enjoy working in interdisciplinary and