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to up to 30 kHz leads to the massive production of data, for which fast (even quasi-instantaneous) processing via neural networks is crucial. Objectives and expected results: The PRICELESS PhD project
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Institut de Recherche pour le Développement (IRD) | Montpellier, Languedoc Roussillon | France | 4 days ago
Optional Skills / Knowledge Expertise in statistics Expertise in high-performance and parallel computing Expertise in neural networks Personal Qualities Intellectual curiosity Autonomy Adaptability Rigor
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27 Mar 2026 Job Information Organisation/Company CentraleSupélec Rennes campus Department Smart Energy Department Research Field Engineering » Electrical engineering Computer science » Modelling
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PhD Positions Application Deadline 3 Mar 2026 - 20:00 (Europe/Paris) Country France Type of Contract Temporary Job Status Full-time Offer Starting Date 1 Apr 2026 Is the job funded through the EU
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insufficiently understood from a mechanistic and modelling perspective. This PhD project aims to develop innovative mathematical and computational models that describe how trees exchange carbon, water and
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and
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SPHERE You have a PhD degree in Artificial Intelligence, Computer Science, Applied Mathematics or in a related field You have at least 3 years of postdoctoral research experience or R&D experience in
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May 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description
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for Languages) essential Strong programming skills in scientific computing languages (e.g. Python, C++) Solid knowledge of microgrid concepts and distribution network operation Knowledge of electric vehicle