51 computer-processor-phd Postdoctoral positions at Technical University of Munich in Germany
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, or machine learning is also appreciated. PhD: The candidate is expected to have some background in theoretical computer science, including some of the following areas: automata, logic, games, verification
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and interest in one of the following fields: • Solid state quantum information science. • Quantum optical properties solid-state systems (e.g. semiconductor quantum dots, colour centers in wice gap
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-quantum cryptography and coded computing (1 postdoc, 1 PhD, Antonia Wachter-Zeh, antonia.wachter-zeh@tum.de) • Theory for communication systems beyond Shannon's approach (1 postdoc, 1 PhD, Christian Deppe
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control and strong interest to further develop their skills. The selected applicants are expected to have: • Masters or PhD-level degree in Robotics, Mechatronics, Computer Science or closely related fields
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skills further, there is also the opportunity to aid in the planning, organization, and running of lectures. Required training, skills, and background • PhD degree in bio/medical engineering, materials
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computer aided methods. Qualifications and Experience • Outstanding academic degree in materials science, metallurgy, metal physics or similar degree • Excellent doctorate with focus on computational
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-funded project TOADAPT, which investigates the social-ecological adaptive capacity of forests across multiple scales and disturbance regimes. Your profile Completed PhD in forest ecology, environmental
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” are ready to be exploited. • You will also be involved in the training of students. Your qualifications and skills: • You have a PhD or equivalent degree in biology, agri-cultural biology or any related field
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following areas: Mathematical Analysis/ Numerical Analysis/ Theoretical Machine Learning Please note: Applications from candidates with degrees in other disciplines (e.g., Computer Science, Engineering) will
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for livestock systems in East Africa, and in the subtropics in Latin-America. The research programme will examine productivity of grasslands, nutrient stocks and cycling and their relationship to biodiversity. We