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, an ambitious programme developing the next generation of intelligent railway adhesion-management technology. RAPID is addressing one of the railway industry's most significant operational and safety challenges
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to the project): PhD in Computer Science, Distributed Software Architectures, Artificial Intelligence, or a related discipline. Strong research background in data management, including policy governance or data
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21 Sep 2026 Job Information Organisation/Company Technical University of Munich (TUM) Department School of Social Sciences and Technology Research Field Computer science Economics Juridical sciences
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this selection procedure, one (1) position equivalent to that of PhD Researcher is open in the area of Computer Science, sub-areas of Artificial Intelligence, Serious Games and Medical Image Processing. The work
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Starting Date 4 Aug 2026 Is the job funded 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
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equivalent to that of PhD Researcher is open in the area of Rehabilitation Sciences – Human Movement System Rehabilitation Specialization. The work will be related to the development of intelligent systems
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Research Framework Programme? Not funded by a EU programme Reference Number QUANTUM_IBER_IA – BI – 02/2026 (1) Is the Job related to staff position within a Research Infrastructure? No Offer Description
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the attribution of one (1) research grant within the scope of LASI - Intelligent Systems Associate Laboratory, reference LA/P/0104/2020, financed by national funds under the Multi‑Year Funding Program for R&D Units
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of the following courses: - PhD in Informatics, Chemical and Biological Engineering, Biomedical Engineering; - Non-degree course. Requirement for granting the fellowship: The applicants may apply without prior
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of one (1) research grant within the scope of LASI - Intelligent Systems Associate Laboratory, reference LA/P/0104/2020, financed by national funds under the Multi‑Year Funding Program for R&D Units funded