136 cloud-computing-"https:"-"https:"-"https:"-"https:"-"UCL"-"UCL"-"UCL" PhD positions in Germany
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“Stability and Solvability in Deep Learning”. This project focuses on mathematically analyzing machine learning algorithms with a particular focus on questions of stability, computability, and robustness
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tools to evaluate the ecological role of parasites and virus in the Elbe Estuary. The work is carried out as part of the DFG Graduate Program “Biota-Mediated Effects of Carbon Cycling in Estuaries
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molecular tools to evaluate the ecological role of parasites and virus in the Elbe Estuary. The work is carried out as part of the DFG Graduate Program “Biota-Mediated Effects of Carbon Cycling in Estuaries
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team. You will be enrolled in the TUM Graduate School with its structured doctoral program and professional-skills courses. You will contribute to an French-German collaboration on next-generation
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use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission analysis, and infrared thermography. Industry
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Oceanography, Marine Geology and Marine Observations work interdisciplinary within a joint research program. The doctoral thesis will be based in the working groups Organic Trace Substances (Organic Trace
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available in the further tabs (e.g. “Application requirements”). Programme Description In line with its statutes, the Studienstiftung des deutschen Volkes (German Academic Scholarship Foundation) supports
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degree (Master or Diploma) in aerospace engineering, mechanical engineering, computer science or a comparable field. • Experience in machine elements, structural analysis, fault diagnosis, and knowledge
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available in the further tabs (e.g. “Application requirements”). Programme Description As part of the HessenFonds, the Hessian Ministry of Higher Education, Research, Science and the Arts provides
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available in the further tabs (e.g. “Application requirements”). Programme Description The PhD scholarships support highly qualified junior academics from the historical sciences with excellent academic