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self-adaptation capabilities. Three major challenges have been identified: (P1) modelling uncertain environments where robust, weakly supervised machine learning algorithms can be deployed to irrigate
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Polytechnique de Paris. The group conducts research at the intersection of statistical learning, machine learning, and data science, with a strong focus on structured data, representation learning, and
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19 Dec 2025 Job Information Organisation/Company UNIVERSITE DE TECHNOLOGIE DE COMPIEGNE Department Biological Engineering Department Research Field Biological sciences » Biological engineering
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Requirements Research FieldComputer science » Computer systemsEducation LevelPhD or equivalent Skills/Qualifications Knowledge • Solid understanding of machine learning, deep learning, and modern AI techniques
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FieldMathematicsYears of Research ExperienceNone Additional Information Eligibility criteria The position requires a PhD in machine learning, NLP, causality, or a related discipline, with a strong command of deep
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or equivalent Skills/Qualifications - PhD in bioinformatics or related subjects - Expertise in python coding - Experience and good understanding of neural networks and machine learning - Fluent written and spoken
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Vision Profiler (UVP), and to analyse its spatial and temporal variability. This will be done by combining different data sources and machine learning (ML). Data used for this ML approach include - a
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on the plants Arabidopsis thaliana will generate maps of depolarization, retardance, dichroism, and optical axis azimuth, which will feed machine learning models developed by the project partners to identify
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22 Oct 2025 Job Information Organisation/Company Universite de Montpellier Department Human Resources Research Field Biological sciences Technology » Computer technology Researcher Profile
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 2 months ago
-adaptive phenomenon. PhD Thesis, Massachusetts Institute of Technology, 1990. [3] A. MacLean, K. Carter, L. Lövstrand, and T. Moran. User-tailorable systems: pressing the issues with buttons. In Proceedings