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diversity outreach. We will help you grow a competitive and international career profile. You will also be part of the materials science ecosystem at TU Munich (e-conversion excellence cluster, Munich Data
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/datenschutz/Bewerbung/. By submitting your application you confirm to have read and understood the data protection information provided by TUM. Technische Universität München TUM School of Engineering and
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informatics, data science, or related subjects, • with a strong passion for entrepreneurship and/or family business research, • with a solid knowledge of empirical research (e.g., quantitative or experimental
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talented individuals passionate about AI, Human-Computer Interaction, Eye-Tracking, and their responsible applications. Ideal candidates will have: • An M.Sc. degree (or equivalent) in Computer Science, Game
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TCR diversity is extremely high (>> 108), and it is not yet possible to precisely predict targets from TCR sequence data. Deciphering the ‘TCR recognition code’ is currently one of the most thrilling
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Advanced software development and data analytics skills Hands-on mentality with first practical experience in developing innovative technology Inquisitive and passionate about research and knowledge transfer
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wellbeing. They will use modeling approaches to combine natural and social science data. You will focus on developing and implementing mixed modeling approaches to test pathways through which structure
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, (electro)chemical engineering, mechanical engineering, materials science & engineering, or a related field. They should be familiar with the working principles of photoelectrochemical energy conversion
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engineering, computer engineering or a related field. Knowledge in the area of mobile manipulation and control of autonomous vehicles. Hands-on experience with developing autonomous and mobile robotic systems
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03.04.2024, Wissenschaftliches Personal Postdoc Green Hydrogen Financing (m / f / d) at the TUM School of Social Sciences and Technology, Professorship for Public Policy for the Green Transition