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Field
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Exactly: A Bayesian Approach. The project aims to address the challenges in pooling inference, by developing and implementing either exact or asymptotically exact Monte Carlo algorithms in collaboration
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reinforcement learning for large language models (LLMs). Research directions include developing next-generation post-training algorithms, exploring diffusion-based approaches to reasoning with language models
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Disse), the Chair of Geoinformatics (Prof. Thomas H. Kolbe), and the Chair of Algorithmic Machine Learning & Explainable AI (Prof. Stefan Bauer). The project aims to develop an integrated urban flood
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. The activities within the project will benefit from synergies with other projects in the group as well as with other activities at the department. The main supervisor will be Assoc. Prof. Francesco Da Ros, DTU
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(FELIX) for ATLAS detector systems. The group also has a strong record in track reconstruction, flavour tagging algorithm development as well as physics data analysis, with a focus on Higgs boson physics
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collaboration with the Intelligent Maintenance and Operations Systems (IMOS) Laboratory at EPFL (Prof. Olga Fink). IMOS focuses on the development of intelligent algorithms designed to improve the performance
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, efficient and context-aware, creating the foundations for the next generation of wearable and augmented reality platforms. The research focuses on developing novel ML methods that learn from limited resources
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benefit. The doctoral project will be carried out between the ETIS laboratory (UMR8051), under the supervision of Prof. Iryna Andriyanova, and the LPTM laboratory (UMR8089), under the supervision of Prof
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to test and demonstrate the developed concepts and algorithms for integrated (re)planning. This PhD research will use a mixture of techniques from logistics, operations research, multiple-criteria decision
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-body positron emission tomography (PET) with magnetic resonance imaging (MRI). In conjunction with the development of algorithms, dedicated software and hardware-based simulations will be developed