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, their achievements and productivity to the success of the whole institution. At the Faculty of Mathematics, Institute of Scientific Computing, within the Dresden Center for Computational Materials Science (DCMS
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German. Prospective applicants should check with the relevant faculty about their requirements. Programme duration 6 semesters Beginning Winter semester Application deadline Applications have to be
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Applicants must provide proof of their German OR English skills. German: TestDaF 4 or DSH 1 or equivalent English: TOEFL 550 (paper-based), 213 (computer-based), 79 (Internet-based) or equivalent Application
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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
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. You also have knowledge of basic molecular biology/biochemistry. You fit to us: if you have a strong scientific curiosity and motivation. if you enjoy interdisciplinary teamwork at the interface
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, and Computational Life Science. The individually tailored training programme and the intensive supervision by interdisciplinary thesis committees guarantee excellent educational standards. Course
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partners across Europe to deliver a world-class doctoral training programme in risk assessment, resilience engineering, and smart technologies. Its scientific vision targets: (1) the development of a
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a world-class doctoral training programme in risk assessment, resilience engineering, and smart technologies. Its scientific vision targets: (1) the development of a holistic multi-hazard risk
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Max Planck Institute for the Study of Societies • | Koln, Nordrhein Westfalen | Germany | about 12 hours ago
publishing or teaching and applying for postdoc positions Students who attend our programme investigate the crucial intersection between the economy, politics, and society and develop new approaches in
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a world-class doctoral training programme in risk assessment, resilience engineering, and smart technologies. Its scientific vision targets: (1) the development of a holistic multi-hazard risk