295 computer-science-programming-languages-"St"-"University-of-St"-"St" positions at DAAD
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Financing yes Type of Position Full PhD Working Language German English Required Degree Master Areas of study Husbandry, Agricultural Science, Geosciences, Environmental Science, Nature Conservation
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available in the further tabs (e.g. “Application requirements”). Programme Description The KAAD is the scholarship institution of the Catholic Church in Germany. Applicants are therefore of catholic
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) and should be used for a doctorate. Participation in the accompanying doctoral program is compulsory. This serves to impart both scientific and methodological knowledge and offers the opportunity
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on methods development in machine learning, uncertainty quantification and high performance computing with context of applications from the natural sciences, engineering and beyond. It is embedded in
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available in the further tabs (e.g. “Application requirements”). Programme Description Women Involvement in Science and Engineering Research (WISER), a programme by the Indo-German Science and Technology
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or very good university degree (diploma, master's degree) in transport or related study programs (e.g., civil engineering, industrial engineering, computer science, etc) with a solid foundation in transport
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Helmut-Schmidt-Programme (Master’s Scholarships for Public Policy and Good Governance - PPGG) • DAAD
list of countries), who want to promote democracy and social justice in their home countries. The programme, which is funded by the German Federal Foreign Office, offers the chance to acquire a Master’s
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qualification program incorporating hybrid lectures, weekly seminars (hybrid and on-site), lab rotations and hands-on training annual summer/winter schools and complementary skills workshops TUD strives to employ
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theory and code development. Basic programming skills are expected. General requirements: very good university degree (M.Sc. or equivalent) in chemistry, physics, or materials sciences; specialization
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computer science, bioinformatics or related fields Solid understanding of machine and deep learning and relevant frameworks (e.g. Pytorch or Tensorflow, Keras, scikit-learn, OpenCV) Proficiency in Python, Linux and