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track record on one of the following research areas: Trustworthy AI AI for formal methods Formal methods for AI The successful candidate will participate in the activities of the research group led by
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or other large-scale biological data), using statistical methods, pathway/network analysis or machine learning. The candidate will conduct integrative analyses of biomedical datasets, focusing on single-cell
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the formal and functional properties of gestures and their relationship to discourse. - Support for computational modeling: o Contributing to the gesture–speech modeling carried out by Loria, based
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ICT Services & Applications. Your role The PhD position is part of the CART-4D project, a "Made in Luxembourg" collaboration between the University of Luxembourg and ARSPECTRA . The doctoral candidate
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of the methods. The project is carried out in close collaboration with Helical-AI, an industrial partner specialized in large-scale genomic foundation models and HPC-enabled model deployment, ensuring
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for embedded and GPU platforms. Collaborate with ARSPECTRA engineers and surgeons to create a complete AR guidance pipeline : tracking, SLAM, gaze, user interface Your profile PhD in machine learning
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role We are seeking a highly motivated PhD candidate to join the IAS Audacity project AI4TECS, which investigates how advanced AI techniques can enable real‑time identification and treatment of emerging
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an innovative multi-method design, the project integrates: Daily diary and ecological momentary assessment (EMA) approaches In-depth qualitative and immersive fieldwork conducted by the geography team A key
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revisited and new methods of cooperation with UTC's engineering departments developed. Teaching Depending on his/her skills and experience, he/she will be expected to contribute to existing teaching units
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on ARSPECTRA hardware in collaboration with their engineering team Contribute to open-source code, demonstrators and joint publications with ARSPECTRA and clinical partners Your profile PhD in computational