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Fixed term contract | Belvaux | 12 Months Are you passionate about research? So are we! Come and join us The Luxembourg Institute of Science and Technology (LIST) is a Research and Technology Organization (RTO) active in the fields of materials, environment and IT. By transforming scientific...
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, developing knowledge, methods, and transferable software for the simulation and comprehensive sustainability assessment of socio-economic systems. Its purpose is to foster sustainable eco-innovation, through
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along with physiological and behavioural data of test drivers and build explainable predictive models out of it. The research team spams Luxembourg, Europe and the USA and will make use of world-leading
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that provides insights into model decision-making processes. Human-in-the-loop system design: you will develop innovative approaches for integrating human expertise with LLM capabilities, including alignment
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order to better understand, explain and advance society and environment we live in. Your role The PhD student will develop and apply computational multiscale models to investigate brain energy metabolism
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numerical optimization and simulation models. Proficiency in one of the major programming languages such as Python A collaborative team player with a desire to make a personal impact within our
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understand, explain and advance society and environment we live in. Your role Conduct research and prepare a doctoral thesis in metabolic network modelling and computational epigenomics Develop novel methods
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with several industrial and political stakeholders that shape our energy transition. Located at the heart of Europe, the group consists of doctoral and post-doctoral researchers from diverse backgrounds (e.g
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) explainability for autonomous systems (Optional) Experience with simulation environments (e.g., CARLA) or multimodal/LVLM models LanguageRequiremets: Applicants must demonstrate at least B2-level proficiency in
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Language Models for Data-to-Text Problems” and involves the study of technical methods and approaches for adapting large language models to tasks mixing text and structured data, such as statistical report