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Master's degree / PhD programme No Joint degree / double degree programme No Description/content Environmental informatics is understood to be an integrated subject consisting of bio-, eco- and
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materials science, physics, chemistry, electrical engineering (or a similar discipline) with focus on sensorics; experience in data processing and machine learning; experience in 2D materials synthesis and
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enrolled in our research-oriented PhD/doctoral programme. In our optics / photonics and quantum technology programme, we offer: high-end research and education in a world-class scientific environment with
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researchers. This includes, among others, a large wind farm operator, a transmission system operator and partners in electrical power engineering. Your profile Requirements for employment include: a qualifying
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in chemistry, physical chemistry, physics, biophysics, biology, biomechanics, mechanical engineering and electrical engineering work together in the Cluster. The HEiKA Graduate School on “Functional
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Your Job: One essential step towards the ramp-up is the identification of site-specific optimal design of DACS plants, which will be the focus of the advertised PhD. To identify optimal DACS plant
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applications in information technology and are based on electrical, magnetic or optical functionalities. The Department of Nanoelectronics is looking for a PhD Student (f/m/d) Metallic and semiconducting
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exclusively in German. Full-time / part-time full-time Programme duration 8 semesters Beginning Only for doctoral programmes: any time Application deadline Please look at our website for the current application
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Leibniz Institute of Ecological Urban and Regional Development (IOER) • | Dresden, Sachsen | Germany | about 10 hours ago
Dresden University of Technology (TUD) Course location Dresden In cooperation with Dresden University of Technology (TUD) Teaching language English Languages The programme is conducted in English. Full-time
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coding background. You must hold a master’s degree in Computer Science, Electrical and Computer Engineering, Mathematics, or similar. Knowledge in machine learning is desired. We are looking for a driven