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PhD Opportunity in AI-Driven 6G Wireless Communication – Join a Leading Scandinavian Research Group! 🌍Are you ready to take the leap into cutting-edge research? We are seeking a motivated, high
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traders and technologists to push strategies into production What we're looking for PhDs graduating by Summer 2026 or postdocs in quantitative fields such as Mathematics, Physics, Statistics, Electrical
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related to staff position within a Research Infrastructure? No Offer Description About us The School of Neuroscience is UK’s 2nd largest Neuroscience school with over 500 researchers and 200 PhD students
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engineering, and hyperparameter tuning to produce resilient and high-performing models. · PhD in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field Strong track record
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | 30 days ago
Assistant position, with the successful candidate embarking on a PhD programme at LSHTM. It is anticipated that the role will lead to a further 18 month funded opportunity at Max Planck Institute
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computer science, data science, mathematics, or statistics. Practical or theoretical knowledge in automated synthesis/robotics. N.B. The candidates selected for interview will receive a preliminary assignment
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used. AI methods for generating regulatory hypotheses between genes, hormones and physical properties will also be developed. Applicants must have/be close to obtaining a PhD or MPhil in Computational
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of research proposals, co-supervision of researchers and PhD students, organization of events, and coordination of research spaces. Main Duties and Responsibilities Perform the following activities in
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technologists to push strategies into production What we're looking for PhDs graduating by Summer 2026 or postdocs in quantitative fields such as Mathematics, Physics, Statistics, Electrical Engineering, Computer
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& robust control, and learning for dynamics & control. The main task of the PhD student will be to develop sound data-driven methodologies for learning control policies with provable guarantees