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for the autonomous selection of a specific research topic from the areas represented within the group. The group’s interdisciplinary focus includes not only classical topics in numerical analysis, e.g. the analysis
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CIIMAR - Interdisciplinary Center of Marine and Environmental Research - Uporto | Portugal | 9 days ago
First Stage Researcher (R1) Positions PhD Positions Application Deadline 16 Apr 2026 - 23:59 (Europe/Lisbon) Country Portugal Type of Contract Not Applicable Job Status Full-time Hours Per Week 40 Offer
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LanguagesFRENCHLevelBasic Research FieldPhysicsYears of Research ExperienceNone Additional Information Eligibility criteria •PhD in accelerator physics or a related discipline •Training or experience in accelerator physics
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to propose a unique swarm-based counter-UAS approach enabling autonomous generation and continuous adaptation of protective swarm behaviours. We are seeking an outstanding Postdoctoral researcher to strengthen
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are designed to empower (forms of) safeguarded AI specifically with LLMs and T2Is, by O1) mapping PRLs automatically onto representations usable by autonomous agents to engage in debate; O2) using
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combining pulsed excitation with state-of-the-art array detectors and photon time-tagging Implementation of a data analysis framework for robust, autonomous, and real-time data evaluation for FFS Proof
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» OtherEducation LevelPhD or equivalent Skills/Qualifications Holder of a PhD in Biology, Physics, Engineering or related field, you have a real interest in academic research in neuroimaging. You demonstrate
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and Key Distribution, Spectrum Management and Coexistence, Tactile Internet, Earth Observation, and Autonomous Transportation. As far as technical enablers are concerned, we leverage expertise
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developed at TU Delft, which can detect life signs in outer space, enable autonomous navigation and space traffic management and monitor in real-time space weather. These instruments provide challenging
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relationships in next-generation electronic materials. This role involves creating AI models for real-time data analysis, enabling autonomous experiments through active learning and "curiosity-driven" exploration