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their studies in Japan. The same applies to PhD researchers based in Japan in relation to their studies in Europe. This offers the scholarship holders the unique opportunity to exchange skills and
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or for an MSc or PhD (or equivalent) in medical engineering, applied medical sciences, public health, or data science in medicine. It funds students from Germany who wish to carry out research stays, internships
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available in the further tabs (e.g. “Application requirements”). Programme Description The Jeff Schell Fellowship can be granted to MSc and PhD students from all fields of natural science and data science
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(written and spoken English) and presentation skills. • Ability to work in a team, with effective interpersonal communication skills. • Willingness to assist with the supervision of BSc, MSc and PhD work Our
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include the University of Oxford, Imperial College London and Ukrainian and British policymakers. What we look for PhD in a policy-related field (e.g., public policy, political economy, economics, political
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on the nanoscale (previous works e.g.: https://www.nature.com/articles/s41563-019-0555-5). You will also supervise one PhD student who will work on a complementary topic guaranteeing quick output and an ideal
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to build a collaborative scientific carrier in computer science and medical data analysis at a German top-ranked university. Help to acquire, mentor and teach students (e.g., PhD, MSc, BSc, seminar series
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to an international competitive PhD degree and internationally peer-reviewed publications. This includes participation in selected nationally and internationally funded projects of the Chair Group, such as the EU
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presentation skills. • Ability to work in a team, with effective interpersonal communication skills. • Willingness to assist with the supervision of BSc, MSc and PhD work Our offer We offer an interesting and
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. Your qualifications An excellent PhD degree either in Computer Science, Physics, Mathematics or related fields, ideally with a background in quantum theory, quantum computing or quantum machine learning