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Field
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The University of Luxembourg invites applications for a fully funded doctoral position in mathematical and computational modelling within the framework of the doctoral training unit Forest Function
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on human-environment interactions in freshwater ecosystems. The studentship covers fees and stipend for a home (UK) student. There is an urgent need for novel freshwater quality monitoring solutions to help
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: Algorithms, AI & Data Science, Software and Interaction. The atmosphere is collegial and informal. Research of the Music Information Computing group (Professor Anja Volk ) lies at the intersection of computer
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. About the Network: GLYCOCALYX brings together 15 leading European partners in a transnational network, implementing a multidisciplinary and intersectorial research and training programme between
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28 Feb 2026 Job Information Organisation/Company Faculty of Science, Charles University Research Field Geography » Human geography Geography » Regional geography Geography » Social geography
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Offer Starting Date 1 Sep 2026 Is the job funded through the EU Research Framework Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 2 days ago
funds through FCT/MCTES Workplan: Research on humanoid robots interacting with humans Duration: The scholarship will last for 7 months, starting in March 2026. The scholarship contract cannot be renewed
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Medicine Leibniz Institute for Molecular Pharmacology Max Planck Institute of Human Development Teaching language English Languages English (100%) Programme duration 6 semesters Beginning Only for doctoral
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different backgrounds. This position requires that you have graduated at Master’s level in in computer science, media technology, computer engineering, human-computer interaction, visual learning and
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to human and environmental interactions across various sectors such as healthcare, education, and urban planning. The primary aim of this project is to develop Multi-Intelligence Agents (MIAs) that combine