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climate will warm and recover in a net-zero future. As part of this project, you will apply machine learning (ML) methods to discover reduced-order models from data and develop GenAI-based techniques
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of molecular and biological matter using X-ray and neutron scattering. One of the research areas is the development of machine learning (ML) based approaches to efficient analysis of the vast data amounts
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guaranteed. Given the real-time nature of these large complex infrastructures, machine learning techniques can complement more deterministic algorithms to guarantee a reliable operation of the system
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the production of polymer latexes that involves a complex, heterogeneous polymerization system and leads to polymers with a diverse range of structures. This project looks to use machine learning to better target
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the upcoming flood type, e.g. heavy-rainfall flood or rain-on-snow flood. As PhD candidate you will compare several machine-learning based algorithms regarding their ability to predict the flood type based
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information exchange (HIE) Natural language processing in clinical/biomedical domains Mobile health, digital health, human–computer interaction in health Learning health systems, community health informatics
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focus on processing and utilising machine-learning techniques to analyse large volumes of data from sensors installed in Phase 1. The aim will be to merge the QC points and tracking system developed in
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 30 days ago
disseminate the developed methods. Where to apply Website https://jobs.inria.fr/public/classic/en/offres/2025-09574 Requirements Skills/Qualifications PhD in Computer Science, Machine Learning, Bioinformatics
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, fabio.hernandez@uis.no Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/288466/phd-fellowship-in-urban-m… Requirements Research FieldArchitectureEducation LevelMaster Degree or equivalent
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Full Time Posting Number 25FA1242 Posting Open Date 12/15/2025 Posting Close Date Qualifications Minimum Education and Experience This position requires a PhD in Electrical and Computer Engineering or a