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Field
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energy efficiency while keeping the grid reliable and secure. Our research method is engineering-oriented, prototype-driven, and highly interdisciplinary. Our typical research process includes
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of studies, coordination of study implementation, data analysis and interpretation (with a focus on neuroimaging data analysis, usage of AI and/ or computational modeling of psychological processes
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24.02.2022, Wissenschaftliches Personal The Munich Quantum Valley aims at developing a full quantum computing stack, from the application level to the physical quantum hardware. Within
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mathematics, computer science, information technology, electrical engineering, physics, mechanical engineering, or a comparable qualification Sound knowledge of mathematics and physics, especially in the fields
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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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, computer science, mathematics, physics, or a related field with an outstanding academic record. Interest in mathematical signal processing, optimization, and/or machine learning is important. Since
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communication system are modeled using information theory. We wish to investigate how interleaving can reduce the overhead and computational load due to coding coefficients required in classical linear random
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Contributing scientifically to the BMD project, specifically through developing VREs and identifying available biodiversity and environmental data resources relevant for VREs Attending virtual and physical
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the following areas: PhD in mechanical/electrical engineering, robotics, computer science, or a comparable field, Experience in self-reliant managing of research projects (financial and administrative) and
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coordination with Prof. Dr. Harald Sack. Qualifications and Skills: A very good PhD degree in computer science or a comparable discipline. Very good software engineering skills. Excellent written and spoken