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University of Veterinary Medicine Hannover • | Hannover, Niedersachsen | Germany | about 6 hours ago
seminars or participating in doctoral study groups. Students' performance in the courses will be evaluated and documented during the programme by the responsible teachers. The PhD students and their
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Degree Dr rer nat / PhD Geoscience Course location Göttingen Teaching language German English Languages Courses are held in English (75%) and German (25%). Programme duration 6 semesters Beginning
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PhD programme provides outstanding doctoral students with a vibrant, highly interconnected research community and a training structure that develops their talents in a unique combination of high-level
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: Investigate and design optimal computing and communication architectures for hardware acceleration of large-scale machine learning workloads Perform characterization and modeling of electronic and optical
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, informatics, physics or a related field strong expertise in machine learning strong interest in high performance computing on CPUs and GPUs proficiency in Fortran, Python, shell scripting proficiency with Linux
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knowledge of the German language besides English. If interested, please send your full application to the email adress provided below. At the Mechanics & High Performance Computing Group, there is an open
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European and International Studies (ZOiS), German Institute for Economic Research (DIW), German Institute of Global and Area Studies (GIGA), Hertie School – The University of Governance in Berlin, Leibniz
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additional courses offered by other institutions of the University of Freiburg, which may be held in German. Full-time / part-time full-time Programme duration 6 semesters, 8 semesters Beginning Only
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the doctoral programme. A tutor school can be attended to build up one's own teaching skills. Course-specific, integrated German language courses No Course-specific, integrated English language courses
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tunability and high-order dynamics to realize dendrite-inspired functional circuits. These circuits will subsequently be integrated as core computational modules within unconventional computing architectures