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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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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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(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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. 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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, 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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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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groups are strongly encouraged to apply. Your Tasks: Development and application of algorithms for modelling, evaluation and visualization of ultrafast processes Investigation of ultrafast dynamics in
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contribute to the development of novel algorithms and methodologies that enhance the robustness and accuracy of acoustic measurements. We are looking for a highly motivated candidate, with a relevant MSc
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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