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: university degree in chemistry or physics and profound knowledge in computational and theoretical physics/chemistry. Capability of team work is essential. Skills in high-performance computing, materials
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nationality from biological sciences, chemistry, mathematics, computer sciences and physics. Be part of CiM-IMPRS, a program run jointly by the University of Münster and the Max Planck Institute for Molecular
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Description TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in the country. Founded in 1828, today it is a globally
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available in the further tabs (e.g. “Application requirements”). Programme Description International students holding a Master’s degree in (molecular) biology, (bio-)chemistry, physics, mathematics
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was established in 2019 with our partner institute, the Nagoya Institute of Technology, Japan, in order to better understand lead-free perovskite materials for photo-electro-mechanical energy conversion systems
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of computer science, software systems engineering, digital technologies or comparable qualification Openness to varied and exciting topics and tasks in the field of digitized circular economy Independent, structured
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the experimental part of their thesis work from the third PhD year onwards Your Qualifications Minimum requirement: Master’s Degree in Biomedical Sciences, Biology, Biochemistry, Data Sciences, or Bioinformatics
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of computer science, software systems engineering, digital technologies or comparable qualification Openness to varied and exciting topics and tasks in the field of digitized circular economy Independent, structured
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-derived amines for Maillard reaction in Brassica foods – GluAmin’, which is funded by German Research Foundation: PhD student (f,m,div) in the field of food chemistry Reference number: 14/2025/3 The salary
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ranges from core areas of computer science and electronics over medical applications to societal aspects of AI. SECAI’s main research focus areas are: Composite AI: How can machine learning and symbolic AI