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and transformer architectures to unsupervised learning and representation learning approaches. You will work in close collaboration with clinicians, AI researchers, statisticians, and industrial
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be able to track differences in strategy use between novices and experts on a task and map their learning trajectory. What are you going to do? You will be responsible for coordinating and carrying out
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). This interdisciplinary project investigates how AI — specifically large language model (LLM)-based agents — can act as adaptive social agents to support students' collaborative learning in Challenge-Based Learning (CBL
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the content of the science they study. You will be an active member of RCNP. You will collaborate with the other postdoctoral researchers, PhD candidates and senior investigators, participate in seminars and
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broad European and international network through its collaboration schemes and open-science activities. Through its research, the ACT provides ESA with early scientific insight on emerging trends and acts
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Can technology learn to listen to how athletes feel, and not just to what the sensors measured? In the ASPIRE project, we develop knowledge for the new generation of sports tracking technology that
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on text and image feature learning for news ecosystems, analysing the complex multidimensional feature space of visual information to support data-driven journalism. This includes experiments
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to different diseases under abiotic stresses. This postdoc position offers the opportunity to learn the needs for keeping plant breeding innovative in the future, and to apply your research skills in the domain
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structure modeling in cancer immunotherapy design. Profile A — AI PhD in machine learning, computer science, computational science, or a related field. Strong experience with deep learning (e.g., PyTorch
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or more of the following areas: (1) Generative AI and machine learning, (2) affective computing, (3) human-computer interaction or collaborative AI, and (4) interaction design, experimental design or