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Max Planck Institute for Intelligent Systems, Tübingen, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | 22 days ago
ongoing research efforts in the development of statistical 3D models of Horses. About us We are creating the world’s most realistic human and animal avatars for use in research, film, virtual reality
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an artistic development project at a higher education institution in Mecklenburg-West Pomerania are welcome to apply. The PhD scholarships are awarded to graduates with excellent academic achievements who have
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to contribute to sustainable development. To this end, scholarships are granted for development-related PhD studies for individuals who plan to pursue a career in teaching and / or research at a higher education
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range of global ocean biogeochemistry model configurations with enhanced horizontal resolution in the Agulhas region. The precise scientific and methodological focus of the project will be developed
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or electrolyzers, H2O2 production, or electrochemical CO2 reduction. To do so, the stability of newly developed catalysts is of pressing concern. You will continue our research line around stability assessment
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Institute for Industrial Mathematics ITWM, we see our task as further developing key technologies, providing innovative impetus and implementing these in practice together with industry partners. In doing so
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team from Friedrich Schiller University Jena, the Max Planck Institute for Biogeochemistry, the Jena University Hospital, and the Senckenberg Institute for Plant Form and Function jointly develops AI
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mentoring, and it serves as the university’s umbrella organisation for all operative and strategic developments regarding early-stage researchers’ careers. In this context, the Graduate Academy cooperates
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of autonomous vehicle systems. The AVS Lab's research is motivated by the goal of developing the next generation of intelligent autonomous vehicle systems. We are seeking for highly motivated and enthusiastic PhD
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assimilation. The task for the successful candidate is to generate atmospheric fields for given time instances that are as close as possible to a given set of pointwise observations. The candidate will train a