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15.05.2021, Wissenschaftliches Personal The chair of Software Engineering for Business Information Systems (sebis) at the Technical University of Munich is looking for an excellent candidate for a
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. This interdisciplinary PhD is ideal for candidates with a background in chemical engineering, physics, soft matter science, computational chemistry, and/or related disciplines. Early applications are encouraged, as the
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, Mechanical Engineering, Electrical Engineering, Computer Engineering, or a closely related discipline. Strong research interest in telerobotics, shared control, human–robot interaction, or networked control
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student supervision between the physical, engineering and computer sciences, and takes place in the Materials Innovation Factory , the largest industry-academia colocation in UK physical science. The
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the deadline. The project is to contribute to a major Ministry of Defence (MOD) research programme intended to develop generation after next technologies for applications in defence and security, and this
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Network initiative aimed at revolutionizing the field of Quantum Technology by addressing critical gaps in interdisciplinary education and training. This program will cultivate a new generation of “Q-System
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Machine Learning for Image Classification. Eligibility You must: We would like you to have: sound knowledge of machine learning, computer vision and image processing strong programming skills. How to apply
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Environment This studentship is based at the Centre for Vision, Speech and Signal Processing (CVSSP). CVSSP is: The largest UK research centre in its field Ranked 1st in the UK for Computer Vision research
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Optimisation and Operations Research. About the organisation The faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) uses mathematics, electronics and computer technology to contribute
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to enroll in the graduate training programme of e.g. the Netherlands Graduate Research School of Science, Technology, and Modern Culture (WTMC), the Sustainability Transitions Research Network (STRN