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are foreseen, applicants must be ready to travel Applicants must be eligible to enroll on a PhD program at TU Dresden (see https://tu-dresden.de/ing/maschinenwesen/postgraduales/promotion?set_language=en
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environment Scientific excellence and extensive professional networking opportunities A structured PhD program with a comprehensive range of continuing education and networking opportunities - more information
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for a motivated PhD student with a good knowledge of algorithms and theoretical computer science. The successful candidate will take part in the research and teaching activities at the Chair of Algorithms
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environment in the fields of science, technology and administration as well as for the education of highly qualified young scientists. We are seeking two motivated PhD candidates to develop a novel multi-scale
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on conferences and in publications Requirements Master’s degree in physics or chemistry, computer science or equivalent Interest in Physics and Machine Learning Good written and spoken English Ability to work both
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to strive for a PhD. The at the Institute for Software and Systems Engineering (ISSE) located Research Group Digitized Green Tech focusses on the design and the development of digital solutions to shape a
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offer A vibrant research community in an open, diverse and international work environment Scientific excellence and extensive professional networking opportunities A structured PhD program with a
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and scientific work by students Your profile: Successful degree (Master's, Diploma) in the field of computer science, software systems engineering, automation engineering, digital technologies
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of science, technology and administration as well as for the education of highly qualified young scientists. We are seeking a motivated PhD candidate to apply the emerging framework of information field theory
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on performance and project needs. **Qualifications** • For Doctoral Candidates: Master’s degree in Computer Science, Information Systems, or Mathematics. **Applicants must demonstrate:** • An excellent academic