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-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process . An excellent technical infrastructure, on-campus children's day care and sports facilities
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Description Your Responsibilities We are looking for a highly motivated PhD student in the areas of Probabilistic Machine Learning and Neuro-Symbolic AI to contribute to the Cluster of Excellence “Bilateral AI
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command of the English language (knowledge of Dutch is not required). Please note: Each project requires a different mix of skills and attitude. Please use the TU/e PhD Competence Profile to determine
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-physical systems secure and resilient in the presence of uncertainty and cyber-physical attacks? Then you may be our next PhD candidate in resilient and learning-based control of cyber-physical systems
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16 Apr 2026 Job Information Organisation/Company Nantes Université Department SUBATECH UMR-CNRS 6457 Research Field Physics Researcher Profile First Stage Researcher (R1) Positions PhD Positions
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PhD Position – Development of metal-organic frameworks-glass composites for sustainable applications
» Inorganic chemistry Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 30 Apr 2026 - 15:00 (Europe/Brussels) Country Spain Type of Contract Temporary Job Status Full
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-investigator to the BEETHOVEN project. Participation and Completion of PhD courses according to the curriculum Applied Evidence Synthesis in Health Research Educational Contributions: Teach courses in clinical
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position within a Research Infrastructure? No Offer Description Position in the project: PhD Student in Neural Rendering Scientific discipline: Computer Science / Technical Computer Science / Mathematic Job
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conducted according to national guidelines for University and Technical College PhD scholars, and in accordance with the Civil Servant Act, the Security Act, and the Export Control Act. Interested in learning
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preparation and testing or powder mixtures, and then to devise predictive models (possible using machine learning approaches) for the estimation of mixture properties from pure component propeties. The PhD