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TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in the country. TUD has established the Research Training Group
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collaborations with colleagues across domains! Selection criteria A MSc degree in Computer science, Applied Mathematics, Physics, or a related field; Good knowledge of and experienced with machine learning; Good
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. You must submit one application per studentship, you cannot apply for multiple studentships on one application. Contact Details For enquiries, please contact Dr. Libing at libing.cao@ncl.ac.uk You can
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TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in the country. Founded in 1828, today it is a globally oriented
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encourage women to apply. The University is a certified family-friendly university. We welcome applications from candidates with disabilities. If multiple candidates prove to be equally qualified, those with
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, Electrical Engineering, Mathematics, Control theory, Cyber-physical systems, or any other related discipline, potentially with skills in Power Electronics. Applicants who are in the final phase
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PhD Studentship: Multi-robot Cyber-physical Systems for Solar Farm Health Monitoring and Maintenance
universities (The University of Manchester , University of Glasgow and University of Oxford ). Robotics and Autonomous Systems (RAS) is an essential enabling technology for the Net Zero transition in the UK’s
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to interdisciplinary research at the intersection of blockchain technology, economics, and game theory. The focus will be on designing, analysing, and optimising economic mechanisms in blockchain-based systems while
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Research theme: Analysis, geometry and dynamical systems How to apply: uom.link/pgr-apply-2425 No. of positions: 1 This 3.5 year PhD project is fully funded for home students; the successful
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Professor Emma Ahlqvist, you will conduct research focused on cardiovascular disease and precision medicine in type 2 diabetes. We will use statistical and genetic approaches to analyze data from large