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multimodal data. Your responsibilities include: Developing and applying machine learning, deep learning, and LLM-based methods to multimodal clinical datasets e.g. EHR, imaging, omics, sensor data Designing
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of publications Contact information of at least two referees Sketch of planned research, publication activities and ideas for a course design of an introductory course to inclusive education at MA – level (maximum
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focus on Computer Vision, pattern recognition, and visual generative modeling. CVI2 offers the opportunity to contribute to a diverse portfolio of projects, including collaborations with industrial
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primary focus on Computer Vision, pattern recognition, and visual generative modeling. Multiple positions are available. CVI2 offers the opportunity to contribute to a diverse portfolio of projects
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The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character. To be at the forefront of innovation in teaching and learning
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pilots. The role combines experimental device R&D, modelling-supported design decisions, and rigorous measurement work. You will work closely with both academic and industrial supervisors in a small
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Machine Learning, addressing challenges in counter drone swarm formation and defense Design, develop and conduct experiments of drone swarms using both simulation environments and real-world deployments
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(SnT) at the University of Luxembourg is a leading international research and innovation centre in secure, reliable and trustworthy ICT systems and services. We play an instrumental role in Europe by
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translational and scalability considerations. Responsabilities: Lead the development of hybrid foundation model–graph neural network architectures for gene perturbation prediction, including the design and
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and test early warning capabilities in surface water systems Design non-target workflows for the identification of ECs and potential TPs in wastewater Optimize these NT workflows for the continuous >2