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degree of independence and commitment Experience with machine learning and high-performance computing is advantageous, but not necessary Our Offer: We work on the very latest issues that impact our society
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design are often too slow, costly, and inefficient to cope with the increasing complexity of performance and resource-efficiency requirements. This collaborative doctoral project brings together
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University of Veterinary Medicine Hannover • | Hannover, Niedersachsen | Germany | about 19 hours ago
performance in the required courses of the PhD programme will be evaluated by regular testing and confirmed by the supervisor. PhD students determine their individual courses of study in accordance with
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performing local neural pattern recognition and decoding. A low-power transceiver, which will transmit only the decoded high-level control commands instead of the raw data, dramatically reducing bandwidth and
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University of Veterinary Medicine Hannover • | Hannover, Niedersachsen | Germany | about 19 hours ago
participate in the courses, for example by holding lectures during seminars or participating in doctoral study groups. Students' performance in the courses will be evaluated and documented during the programme
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University of Veterinary Medicine Hannover • | Hannover, Niedersachsen | Germany | about 19 hours ago
. by giving lectures during seminars or by participating in doctoral colloquia. A student's performance in the required courses of the PhD programme will be evaluated by regular testing and confirmed by
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demonstrate suitable experience in computer science, machine learning, robotic vision, or a related field (through a high-quality Honours or Masters degree). The successful candidate must be able to enrol as a
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profound knowledge in computational and theoretical physics/chemistry. Capability of team work is essential. Skills in high-performance computing, materials chemistry, theoretical chemistry, molecular
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-value reinforcements in their short and randomly aligned form. A key challenge to the effective reintegration of recycled carbon and glass fibres into high-performance products lies in achieving scalable
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local gas/liquid phase conditions. Whilst direct simulations of breakup are possible, computational cost is high, restricting applications to small sections of geometry and for modest run times