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(at least finished before July 2025) very good programming skills and AI/ML knowledge good written and spoken English skills (CEFR level C1 or higher) We offer: cutting-edge research in data science and
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available in the further tabs (e.g. “Application requirements”). Objective This scholarship programme offers you the opportunity to complete your doctoral degree in Germany. The scholarships are funded by
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depending on the length of the chosen study programme or project Start: usually from 1st October of the following year (depending on the start of your study programme), or earlier if a German language course
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years' professional experience the chance to take a postgraduate or Master's degree at a state or state-recognised German university, and in exceptional cases to take a doctoral degree, and to obtain a
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, Cheminformatics, Computational Biophysics, or a closely related field Strong programming skills (e.g., Python, C/C++) Knowledge of machine learning frameworks (e.g., PyTorch, TensorFlow) Very good English language
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, academics and professionals. What can be funded? Doctoral studies at a German university and, where appropriate, in conjunction with a non-university research Institution. Duration of the funding Up to 48
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English (written and spoken) is essential in order to participate actively in the programme. Further information The programme is jointly organised by the German Academic Exchange Service (DAAD) and the
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available in the further tabs (e.g. “Application requirements”). Objective The primary aim of this programme is to promote the research projects within the context of the doctoral degrees and scientific
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available in the further tabs (e.g. “Application requirements”). Objective The German Academic Exchange Service (DAAD) supports the scholarship programme "Combined study and practical stays for engineers from
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) or earlier if a German language course is taken prior to the study programme The scholarships are awarded for the duration of the standard period of study for the chosen study programme (up to a