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Field
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. Full-time / part-time full-time Mode of study Fully on-site with voluntary online elements Programme duration 6 semesters Beginning Only for doctoral programmes: any time Tuition fees per semester in EUR
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, medical informatics, databases, data mining, machine learning, applied mathematics, biomedical modelling and analysis of complex networks. Joint data science projects between the different partners
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public holidays and weekends (e.g. between Christmas and New Year) Further development of your personal strengths, e.g. through an extensive range of training courses; a structured program of continuing
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Degree Doctorate in Informatics (Dr-Ing or Dr rer nat) Course location Saarbrücken In cooperation with Max Planck Institute for Informatics (MPII) Max Planck Institute for Software Systems (MPI-SWS
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only in English. Full-time / part-time full-time Programme duration 6 semesters Beginning Winter semester Application deadline Applications for the PhD Medical Research – Cardiovascular Science are
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Carl von Ossietzky University of Oldenburg • | Oldenburg Oldenburg, Niedersachsen | Germany | about 20 hours ago
strategies for their present and future careers in science and enterprises. The core of the programme is an independent doctoral research project in one of the participating research groups. In
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management, writing, networking, and career advice and coaching. Course organisation The PhD training programme combines mandatory elements required for all doctoral candidates within GEAS with methods and
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in interdisciplinary networks alike. The BMC of the LMU is located on the Martinsried Campus (one of the best scientific locations in Germany) and offers an ideal research infrastructure. Off campus
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researchers and to provide you with every possibility for networking. Training: Personalised and Responsive Close personal supervision by three professors Individual and flexible course programme Methodological
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ranges from core areas of computer science and electronics over medical applications to societal aspects of AI. SECAI’s main research focus areas are: Composite AI: How can machine learning and symbolic AI