51 phd-in-computational-mechanics-"KHALIFA-UNIVERSITY" Postdoctoral positions at Technical University of Munich
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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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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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06.12.2021, Wissenschaftliches Personal The professorship of Data Science in Earth Observation is seeking six new PhD candidates/PostDocs for its new center for Machine Learning in Earth Observation
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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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the study of the impact of digital and computational pathology on clinical workflows and patient care. Our lab is located in the heart of Munich at the TUM Klinikum rechts der Isar (MRI), Institute
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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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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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. The aim of our group is to improve the understanding of the trade-offs between production, mitigation and conservation in livestock-based systems, and to identify innovative mechanisms for landscape-level
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the understanding of the trade-offs between production, mitigation and conservation in livestock-based systems, and to identify innovative mechanisms for landscape-level management. Our group combines empirical work