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full-time Programme duration 6 semesters Beginning Only for doctoral programmes: any time Application deadline Any time Tuition fees per semester in EUR None Combined Master's degree / PhD programme No
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international work environment Scientific excellence and extensive professional networking opportunities A structured PhD program with a comprehensive range of continuing education and networking opportunities
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or Postdoctoral position (m/f/d) - Interpretable Machine Learning for Catalytic Reaction Network Discovery. A full-time PhD or Postdoctoral position is available in a collaborative Max Planck research
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Applications are invited to undertake a PhD programme, in partnership with Airbus, to address key challenges in ensuring adoption of sustainable approaches to fuel additives for aviation use
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pathogens effectively. Programme highlights • Four years structured PhD studies in an innovative research project supervised by internationally renowned principal investigators • Integration
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research interests might be considered, priority will be given to those able to relate to one or more of the above topics. Applicants must have a PhD in Mathematics, Statistics or Computer Science obtained
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The AITHYRA-CeMM International PhD Program in AI/ML, Molecular Technologies and Systems Medicine Do you want to work in a creative, free-minded scientific environment at the interface of life
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PhD Position in Theoretical Algorithms or Graph and Network Visualization - Promotionsstelle (m/w/d)
of Munich (TUM), Campus Heilbronn. We are looking for exceptional candidates who are interested in pursuing a PhD in either theoretical computer science or graph and network visualization. We seek PhD
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About the Role The project “An Erlangen Programme for AI” (funded by the UKRI), will broadly involve applying advanced mathematical techniques for understanding training in neural networks, with
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Location: UK Other Applications are invited to undertake a PhD programme, in partnership with Airbus, to address key challenges in ensuring adoption of sustainable approaches to fuel additives