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multimodal signals to improve the performance of multilingual models for low-resource languages, such as Luxembourgish. Particular emphasis will be placed on language-agnostic modalities, including images and
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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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dynamics and biomolecular condensates contribute to PD co-pathologies in human midbrain assembloid models. The work combines advanced imaging, molecular biology, and functional disease modeling. Key
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as part of the CET (Comité d’Encadrement de Thèse) and will be daily supervised by the Postdoc employed in the project by UL. The PhD candidate will join the Mobilab Transport Research Group, a dynamic
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learning models) in these tasks. These investigations include the feasibility, practicality and success evaluation of prototype implementations. More generally, the PhD thesis is part of a large initiative
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that include the feasibility, practicality and success evaluation of prototype implementations. You will be working close together with Mike Papadakis (Associate Professor in Software Engineering). The position