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interdisciplinary research network. The PhD student will be affiliated with the Centre d’études orientalistes / Oriental Institute (CIOL) of the UCLouvain, a vibrant international research environment focussing
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theory? Do you want to develop cutting-edge control algorithms for the security and resilience of cyber-physical systems? We welcome you to apply for a PhD position in the SecReSy4You Doctoral Network, a
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PhD position in Economics as part of the renewed RESA Chair, dedicated to studying the future of natural gas networks in the context of the European energy transition. JOB DESCRIPTION The PhD candidate
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with international partners Qualifications To be admitted to the PhD programme at the Faculty of Medicine, applicants are required to have completed at least 5 years higher education, i.e. a master’s
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PhD position in Adaptive Protocols for Decentralized Wireless Networks - Secure Mobile Systems Group
19 Mar 2026 Job Information Organisation/Company IMDEA Networks Institute Department Secure Mobile Systems Group Research Field Computer science » Other Engineering » Electrical engineering
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Jaguar Land Rover, this research proposes the Ring Probabilistic Logic Neural Network (RPLNN). Unlike opaque deep learning models, the RPLNN fuses neural computation with probabilistic logic rules within a
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Engineering » Other Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 4 May 2026 - 23:59 (Europe/Lisbon) Country Portugal Type of Contract Other Type of Contract Extra
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19 Mar 2026 Job Information Organisation/Company IMDEA Networks Institute Department Secure Mobile Systems Group Research Field Computer science » Other Researcher Profile First Stage Researcher (R1
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through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Environment The work of the PhD
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, and space hardware. This PhD research aims to develop a comprehensive Mode Selection Framework for Reduced Order Modelling (ROM) in Structural Dynamics—using machine learning to build robust