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Contributions - A formal framework for modeling well-being in adaptive learning - A well-being-aware student simulation model - A multi-objective RL framework - An orchestration architecture - Experimental
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expertise in HCI and education, including adaptive gamification, engagement, learning analysis, and the design of motivational affordances in education. As part of the project, the PhD student will work with
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Description The overarching mission is to conduct research combining machine learning, data assimilation, and physical modeling to enhance short-term (days/weeks) forecasts of Arctic sea ice conditions. The
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new thermoelectric materials using data science and machine learning methods applied to materials, based on expert-reviewed experimental data from the literature and public databases (notably
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Research Framework Programme? Horizon Europe - ERC Is the Job related to staff position within a Research Infrastructure? No Offer Description The Machine Learning for Integrative Genomics team (https
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mathematical models using a reasonable number of physical variables; (2) the observations of extreme weather events used in the learning bases of DNNs are much rarer than those of standard events. This induces a
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or Phonetics Basic knowledge of machine learning tools; familiarity with a scripting language Ability to communicate and coordinate with different partners: field linguists, computer scientists, engineers
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, Bash, R/Julia, C++, or similar) and in modelling natural systems, as well as a strong motivation to learn new programming languages relevant to this field. - A solid understanding of the concepts
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, soil, and plants aid in the collection of real-time data directly from the ground. Based on these historical data predictive machine learning (ML) algorithms that can alert even before a problem occurs
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learning. Work carried out during the Master's internship has already identified strong trends and tested statistical and machine learning approaches. The thesis will aim to consolidate and update