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Postdoc: Machine learning for wind flow prediction in coastal dunes Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 36 to 40 Application deadline: 6
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infection in vulnerable infants? Join an NWO Vidi project that combines advanced gut-on-a-chip technology, organoid models and microbiome approaches. You will work in an interdisciplinary setting to establish
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an inclusive, collaborative research culture. What we ask of you You are a curious and rigorous researcher who enjoys learning across disciplines. You can translate an ambitious methodological idea into a
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for accountability, transparency, inclusiveness, and misinformation. The key technology is multimodal deep learning, and its extensions for these additional targets. In particular, we have a large collection of
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demand, hindering scale-up. Information This project will be executed together with company Exergy within the EKKO Circular Plastics project. The PD researcher will develop and validate an AI-enhanced
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, history and philosophy of physics. There is considerable freedom to shape the precise research direction according to your expertise and interests, provided that it contributes to the overarching questions
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antigens presented by MHC molecules. This curiosity-driven project develops cutting-edge AI technology for 3D TCR–pMHC modeling to improve neoantigen identification, TCR specificity prediction, and TCR
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25 Jul 2026 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Engineering » Chemical engineering Engineering » Materials engineering Researcher Profile
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machine learning; acoustic signal processing enhanced by ML; human-in-the-loop/active-learning methods; representation learning; analysing sound sequences and vocal interactions; category discovery; Perma
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, and other societal stakeholders. By harnessing state-of-the-art AI for metadata generation, it enhances the value of existing data, supports ongoing investments in FAIR implementation, and strengthens