44 programming-"the"-"DAAD"-"EURAXESS"-"U"-"UCL"-"RAEGE-Az"-"Prof" positions at Technical University of Munich
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programming experience; apply by sending CV and transcripts to alanwar@tum.de About the Role: Join us to push the state of the art in formal verification and reachability analysis for discrete-space systems
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- Strong interest in research questions linked to marketing, management and psychology - Strong programming skills in C++, C#, OpenXR, Unity, Blender, Unreal Engine - Solid quantitative skills (R, Python
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. Support: Access to TUM’s doctoral program and external opportunities for continuous quantitative training (e.g., GSERM, ICPRS Michigan) and research stays abroad - Environment: Work in interdisciplinary
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an interdisciplinary career skills programme across Europe. The Technical University of Munich (TUM) is one of the best universities in Europe. It is characterised by excellence in research and teaching
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field. They should have a strong background in photoelectron spectroscopy and (photo)electrochemistry. Being familiar with CAD programs and having knowledge of PVD-based thin-film semiconductor
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and networking opportunities within the Munich AI ecosystem and within structured graduate programs: the Munich Centre for Machine Learning (MCML), the Munich Data Science Institute (MDSI), the local
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in production engineering issues and their investigation Enjoyment of supervising and programming technical systems Purposefulness and independent working style Creativity and willingness to experiment
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autonomous systems Fluent English (spoken and written); German proficiency is a strong plus Ability to work independently, willingness to learn and acquire new competence Strong programming skills (Python, C
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related discipline. Strong expertise in medical imaging and/or machine learning. Excellent programming and research skills. Interest in translational research and interdisciplinary collaboration with
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, data science, geoinformatics) - Proficiency in at least one programming language commonly used in the processing of research data (e.g., R, Python), and a solid understanding of ETL processes (Extract