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Max Planck Institute for Biology of Ageing, Köln | Koln, Nordrhein Westfalen | Germany | about 5 hours ago
talented researchers. The structured PhD training programme within a cutting-edge research environment will start on an individual basis between July 1 and October 1, 2026. We offer An outstanding
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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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Collaborative Doctoral Project (PhD Position) - AI-guided design of scaffold-free DNA nanostructures
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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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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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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. 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