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profile PhD (awarded within the last 5 years) of high quality, ideally in machine learning (in the broad sense), complemented by a strong mathematical foundation in probability and/or statistics Research
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computational framework, integrated with deep reinforcement learning (DRL) methodologies for both gene-level and edge-level perturbation control, represents a significant advancement in the computational toolkit
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spoken and written is required The candidat must have a PhD in computer science, machine learning, or computational biology The position is available immediately and will remain open until filled
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Inria, the French national research institute for the digital sciences | Montpellier, Languedoc Roussillon | France | 3 months ago
/public/classic/en/offres/2025-08683 Requirements Skills/Qualifications Python programming. Deep Learning with Python (preferably with Pytorch). Experience with GIS. Experience with NLP would be a plus
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The candidate will have a PhD or equivalent degree in bioinformatics, biostatistics, computational biology, machine learning, or related subject areas Prior experience in large-scale data processing and
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for integration into diagnostic tools Preparing manuscripts for submission to both medical and machine learning journals Qualifications Candidate profile: Required: PhD in mathematics, statistics, data science
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found on hpc.uni.lu . The activities include classical HPC applications such as simulation and modeling, but also artificial intelligence and machine learning, bridging computational science, with data
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, Impresso - Media Monitoring of the Past (https://impresso-project.ch/ ) is an interdisciplinary research project that uses machine learning to pursue a paradigm shift in the processing, semantic enrichment
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the Institute of Applied Physics in Florence, Italy (IFAC) and to conferences in Europe to present scientific results. Knowledge of inverse methods, statistics or machine learning Knowledge of remote sensing from
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integration (including environmental sensors and eye-tracking technologies), strong machine learning and deep learning skills (especially embedding models and spatial data analysis), and experience in