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at the crossroads of AI, machine learning, bioinformatics and genomics, and in developing new methods rather than just applying existing ones, we'd like to hear from you. Website for additional job details https
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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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, understanding and predicting their thermal conductivity from first principles calculations is very challenging. In this doctoral research project, we plan to use machine learning potentials to investigate
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resources of CESAM, including its Machine Learning and Deep Learning hub, • close collaborations with ONERA. The successful candidate will work in a multidisciplinary environment bringing together researchers
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for the analysis of hyperspectral imaging data applied to pictorial layers, based on coupling physical radiative transfer models (two-flux and four-flux approaches) with machine learning methods. The researcher will
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the "Machine Learning and Gene Regulation" team led by William Ritchie, specializing in bioinformatics and post-transcriptional regulation. The scientific environment at the IGH — international seminars, journal
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of 3D crystalline structures; – depending on the candidate's profile, implementing machine learning methods (AI & machine learning) for the analysis of physicochemical data from the hpmat.org database
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- 4 Additional Information Eligibility criteria • Experience in computer modeling and programming • Knowledge of associative learning at both the neurobiological and psychological levels • Experience
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the ANR SOMEDHY project. For more information, see: https://scanr.enseignementsup-recherche.gouv.fr/projects/ANR-25-CE50-55… -Synthesis of molecular complexes with various metal elements (tantalum, iridium
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e.g., ultra-cold gases of bosonic or fermionic atoms, machine learning technologies and quantum computing. At the same time, we work in close connection with IJCLab experimentalists, particularly