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LVLMs for autonomous driving. Objectives Design, develop, and evaluate novel method(s) to detect and localize hallucinations in LVLM outputs for autonomous driving tasks Investigate and propose mitigation
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currently lack reliable uncertainty estimates, limiting error detection and automation. The UMLFF project aims to develop next-generation MLFFs with built-in uncertainty predictions to enable safe, automated
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agenda on multimodal and multilingual language models. The successful candidate will focus on the development of multimodal, multilingual resources and on the design and evaluation of methods that leverage
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, public authorities in their decisions and businesses in their strategies. Do you want to know more about LIST? Check our website: https://www.list.lu/ How will you contribute? You will develop a multi
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, www.uni.lu ), offering broad methodological training and transferable expertise. Your Responsibilities: Conduct research in the field of Multiscale Computational Methods for novel metamaterials as described
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We are looking for a highly motivated PhD candidate interested in AI-based methods, including machine learning and language technologies, for the integration and analysis of clinical, advanced data
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factors. The LCSB recruits talented scientists from various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently
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! Education · PhD in computer science, engineering, applied mathematics, physics, or another STEM discipline. · Demonstrated experience with mathematical and numerical optimization methods
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, economics, and other fields, united by a shared commitment to advancing sustainable technologies that benefit society. For more information, please visit our website: https://www.uni.lu/snt-en/research-groups
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expertise. Your Responsibilities: Conduct research in the field of Multiscale Computational Methods for novel metamaterials as described above Develop theories, methods and computational tools Participate in