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solid experience in programming, particularly in Python and JavaScript. Significant experience in data science and machine learning will be highly valued. You like to work in a team while demonstrating
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» AlgorithmsYears of Research ExperienceNone Additional Information Eligibility criteria - PhD in one of the following areas (or related fields): * Machine learning / deep learning * Quantum computing / quantum
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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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to collaboratively train machine learning models without sharing their data. Instead, clients exchange local model updates with a central server, which uses them to improve a global model. While this paradigm enhances
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ExperienceNone Additional Information Eligibility criteria - Holding a doctoral degree in particle physics - Experience in C++ and Python programming is desired - Experience in training and using Machine Learning
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(I3S), Sophia Antipolis Hosting lab: I3S & INRIA UniCA Apply by sending an email directly to the supervisor: emanuele.natale@univ-cotedazur.fr Primary discipline: Machine Learning Secondary discipline
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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | 12 days ago
Cancer Research Center. The team has access to several computing facilities (e.g. IGRIDA cluster) and established collaborations with other Inria/Irisa research teams in the field of machine learning. Our
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Université de Bordeaux / University of Bordeaux | Villenave d Ornon, Aquitaine | France | 9 days ago
genomic diversity and genetic load from available genomic data for various woody species. For this, you will use the available pipelines from phase 1 of the project and apply machine learning-based methods
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Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | 14 days ago
surrounded by the Alps mountains, offering a high quality of life and where you can experience all kinds of mountain-related outdoor activities. Subject context Supervised learning, successfully training
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). • Advanced quantitative analyses (machine learning, computer vision, multilevel statistics). • Creation and use of Python code for advanced analyses. • Management and monitoring of complex transgenic lines