63 engineering-computation-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" PhD scholarships at Technical University of Munich
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interaction-rich scenarios. Ideal applicants will have a strong M.Sc. in machine learning, control, or safety, and hands-on experience with robotics. Apply now: https://lnkd.in/dNjmv835. Deadline: ASAP. We
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management of bridge portfolios. You will create tools that transform complex data into reliable insights for infrastructure safety and sustainability. The project is a collaboration between the Engineering
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Profile The ideal applicant has a strong background in bioinformatics or computational chemistry, as well as data analysis and solid English-language skills. Experience with programming is highly
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University of São Paulo, Brazil. This position focuses on developing advanced computer vision methods and hardware setup for detecting and predicting plant diseases in soybean cultivation. About Us The Chair
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. To this end, methods are first to be developed and established. Your Profile You ideally bring the following with you: • Excellent master's degree in food chemistry, food technology, biochemistry, biophysics
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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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Universitätsklinikum rechts der Isar der TU München Ismaninger Str. 22, 81675 München http://kornlab.med.tum.de The position is suitable for disabled persons. Disabled applicants will be given preference in case
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your research at conferences, workshops, and through scientific publications. Your profile: ▪ You hold an MSc degree in physics, engineering, or computer science. ▪ You are very experienced in Python
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conferences and workshops, and supporting the team in preparing grant applications. You will also be expected to contribute to teaching in our master's program and assist in supervising bachelor's and master's
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(https://soilsystems.net/ ), a Priority Programme (SPP 2322) funded by the Deutsche Forschungsgemeinschaft (DFG; German Research Foundation). Within SoilSystems, scientists from different disciplines from