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-Machine Interfaces (eHMIs) can enable safer and more inclusive interactions. You will: Develop a theoretical framework for identifying key characteristics of AV–VRU interactions and define design criteria
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, clinical data and AI-driven modelling for cancer research! In this role, you will bridge the gap between machine learning, computational biology, and haematological oncology. You do not need to arrive as an
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23 Jul 2026 Job Information Organisation/Company University of Twente (UT) Research Field Educational sciences » Education Educational sciences » Learning studies Researcher Profile First Stage
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PhD candidate you will develop new ways to extract cosmic-ray physics from KM3NeT data. You will design and characterise reconstruction methods—both machine-learning-based and traditional
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design and characterise reconstruction methods—both machine-learning-based and traditional—for the bundles of muons that reach the detectors, and apply them to data and simulations to constrain cosmic-ray
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closely related discipline). You have a strong interest in AI/machine learning, data mining, regression analysis, responsible AI, causal inference, and programming (R/Python, SQL). Moreover, you are driven
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20 Aug 2026 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Engineering » Computer engineering Engineering » Electrical engineering Researcher Profile
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of years are investigated by combining fieldwork, lab work and computer simulations. By bringing together our fundamental understanding of system Earth and our fresh curiosity we conduct research that is
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strong affinity for language data; solid programming skills (e.g., Python) and experience with machine learning or NLP, ideally including transformer-based models and word embeddings; excellent English
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profiles. Identification of molecular signatures in platelet disorders and bleeding disorders of unknown cause (BDUC). Development of machine learning models for patient stratification. Integration