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Helmut-Schmidt-Programme (Master’s Scholarships for Public Policy and Good Governance - PPGG) • DAAD
list of countries), who want to promote democracy and social justice in their home countries. The programme, which is funded by the German Federal Foreign Office, offers the chance to acquire a Master’s
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towers; Participation in the elaboration of requirements; Development of a 3D vision system; Processing using artificial intelligence; Fusion of depth maps to obtain point clouds and visualization
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value candidates with interest and/or experience in the following areas: a) Understanding of machine learning techniques, with interest in exploring algorithms such as regression, decision trees, Random
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hands-on experience with Python and ML libraries (PyTorch/TensorFlow) experience with signal/image processing or computer vision for video strong programming and data engineering skills Desirable
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degree from a University in NZ. Availability Available to New Zealand Citizen or Permanent Resident Students Our website uses tracking technologies to learn how our visitors interact with our site so that
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supports trainees in learning surgical steps. Alice Ferguson-O'Brien majored in cognitive science and philosophy. She works with Arctic Mayors' Forum, where she helps ensure local leaders across the Arctic
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(20th of July 2026). Academic background: You must have an honours degree or demonstrated equivalent research expertise in computer science, machine learning, data science, human-computer interaction (HCI
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support, advice and what to expect living and studying as an international student at the University of Melbourne. Learn more How can we help? Find a scholarship View scholarship guide FAQ Contact us
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 29 days ago
– Machine Learning for Quantum Simulation and Computing and Thermal Energy and Process Engineering are looking for a PhD Student (f/m/d) in Quantum Algorithms for Droplet and Bubble Oscillation Dynamics
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. State-of-the-art digital models and AI tools that incorporate machine learning could enable predictions of the dry fibre forming that are subsequently used as input into the RTM process model. The EngD