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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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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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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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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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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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of young people. In Luxembourg’s highly diverse society, there is an urgent need to understand how social background shapes life chances: your work will speak directly to that. You will also help design and
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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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(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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(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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Designing hierarchical graph‑based models to predict toxicity under uncertainty by linking molecular‑level and system‑level knowledge Advancing causal inference methods to predict transformation products