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. The PhD project is part of an interdisciplinary collaboration with the University of Bayreuth (EASI lab, led by Prof. Dr. Lisa Hülsmann). Main responsibilities include joint field work to establish an in
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training programme (application deadline: autumn) and a Master's fellowship programme (application deadline: 15 July). Tuition fees per semester in EUR None Combined Master's degree / PhD programme No
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analysis). Preparation of manuscripts for peer-reviewed journals and presentations at conferences. Active collaboration with an interdisciplinary team in microbiology research. Our requirements: Master
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RPTU University of Kaiserslautern-Landau • | Kaiserslautern, Rheinland Pfalz | Germany | about 16 hours ago
forwarded for direct admission. In this case, you can submit your application at any time. https://phd.cs.rptu.de Tuition fees per semester in EUR None Combined Master's degree / PhD programme No Joint degree
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on our How to Apply webpage. Tuition fees per semester in EUR None Combined Master's degree / PhD programme No Joint degree / double degree programme No Description/content At the Hertie School, PhD
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Requirements: excellent university degree (master or comparable) in computer engineering or electrical engineering a strong background in digital design, hardware description languages (e.g. Verilog, VHDL
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models on edge devices Reporting findings and methods in conference and journal papers Your profile Masters, Diploma or equivalent degree in IT/computer science/statistics/applied mathematics/data science
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partners. Your qualifications: Successfully completed Master's degree in the field of meteorology, or related disciplines such as physics, engineering or geosciences. High level of motivation and willingness
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requirements must be met? Doctoral candidates or participants in a combined Master and PhD programme who commenced their studies at least one year before. Doctoral students with a confirmed job offer for after
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Master's theses participation in national and international research projects The position comes with access to high performance computing resources and access to training opportunities within ScaDS.AI