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• Scientific publishing Your qualifications: • Completed academic university degree (university diploma / M.Sc.) in Computer Science, Geoscience, Physics, Data Science, or comparable subjects • Experience in
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the testing of newly devel-oped materials and the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission
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and Master’s students in Informatics and Data Science. Supervise Bachelor’s and Master’s theses. We Offer Practice-oriented research projects with leading academic and industry partners (like Google
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Engineering, Operations Research, Civil Engineering, Computer Science, Data Science or a related field, from a university/department with a strong international research reputation Strong mathematical and
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for probing chemistry at surfaces and interfaces [1]. We want to strengthen this research direction by i) developing a second generation of NV-based NMR spectrometer and ii) applying it to material/energy
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, degree certificates) in a single PDF to the head of the Chair group, Professor Johannes Sauer (jo.sauer@tum.de) by the 30th of September 2023. For additional infor-mation on the projects and the position
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that are technically well-grounded and at the same time represent stakeholder preferences. The integrated Research Training Group (RTG) will provide doctoral researchers with an attractive qualification program, foster
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16.09.2025, Wissenschaftliches Personal Niki Kilbertus invites applications for a fully funded PhD position. We’re looking for a creative and motivated individual passionate about developing ML methods to tackle challenges in scientific modeling. Affiliations: Technical University of Munich...
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23.07.2025, Wissenschaftliches Personal The Ecosystem Dynamics and Forest Management Group at the TUM School of Life Sciences, Technical University of Munich studies how forests change in time and space. We quantify these changes, identify their causes and describe their impacts on biodiversity...
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profile: • Very good degree (Master or Diploma) in aerospace engineering, mechanical engineering, computer science or a comparable field. • Experience in machine elements, structural analysis, fault