102 computational-physics-"https:"-"https:"-"https:"-"https:" positions at Technical University of Munich
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involve the integration of: Advanced motion planning and control algorithms Multi-modal perception techniques (e.g., vision, tactile, force) Machine learning models for physical behavior prediction and
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leader with a focus on data and AI Science to join us as soon as possible. Your qualifications PhD in Computer Science, Mathematics, Physics or related fields Experience in applied data science and machine
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, multi-component molecular chaperone machines and the question how membrane protein chaperones recognize and process clients on a molecular level. The project has the potential to provide exciting new
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and publications, there is the possibility of international research stays and conference travel. Benefit from a comprehensive training program covering both subject-specific and interdisciplinary
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for quantum computers and develop methods and software tools dedicated to the design and realization of quantum algorithms/circuits. We see ourselves as an interface between the stakeholders building physical
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at the interface of quantum information, condensed matter and high-energy physics. A strong background and interest in one or more of the following topics is desirable: - Quantum computing with qudits, quantum error
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publications and open-source research software. Your Skills and Professional Profile (required) Master’s degree in robotics, mechanical engineering, electrical engineering, computer engineering, or a closely
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Informatics, specifically for a DFG project in wind power forecasting using machine learning. You are passionate about applying cutting-edge information technology to solve the energy and climate crisis and
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29.09.2025, Academic staff About us The Professorship for Computer Architecture and Operating Systems at TUM Campus Heilbronn covers a broad range of research focus areas in computer architecture
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chaperones and the question how membrane protein chaperones recognize and process clients on a molecular level. The project has the potential to provide exciting new insights in the molecular biology of cells