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knowledge of extracting (event) data from text, documents, and/or media articles or implementing large-N analytics and algorithms, preferably LLMs and/or NLP. Conduct collaborative and independent research
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build relationships. The present project aims to build and test in a Multicentric approach, a digital architecture to support a “personalised digital follow-up environment” . This is based on data
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programming, statistics, machine learning and big data approaches in the context of soil-vegetation-atmosphere interactions excellent writing and oral communication skills in English and strong ambition
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National Growth Fund-funded research project ‘Re-Ge-NL Opens external : Accelerator for the transition to a regenerative, profitable and socially supported agricultural sector’ in which a large consortium
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Postdoc in computational social choice for large-scale deliberation (1.0 FTE) (V25.0203) « Back to the overview Job description A 2-year postdoc position in computational social choice for digital
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Foundation of Scientific Research Institutes (NWO-I) - the institute pillar of the NWO - and a large national consortium involving the NWO-I, Radboud University, Delft University of Technology, Maastricht
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uncovering companion biomarkers for precision treatment using cutting-edge bioinformatics and proteomics approaches. You will analyze bulk and clonal protein expression data from large melanoma cohorts
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Department of Analytical Chemistry and Chemometrics, where we transform chemical data into valuable insights for industrial sustainability using the newest hybrid AI. Collaborate on exciting projects with
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expertise in data science, with hands-on experience in techniques such as machine learning, reinforcement learning, and simulations, and in handling large-scale, within-person, or real-time datasets; A strong
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bulk and clonal protein expression data from large melanoma cohorts, integrate molecular, histological, and clinical data through machine learning (ML)/AI-assisted methodologies. Your expertise in ML