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clinical research center is a plus; Knowledge and experience of machine learning methods; Constructive attitude, flexibility, outgoing and service oriented; Excellent communication, negociation and
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technologies, and integrate machine learning-driven digital twins for predictive combustion modeling. The research program will cover a wide range of e-fuels (H₂, NH₃, CH₃OH, DME, OME) and their applications in
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-flexible technologies, and integrate machine learning-driven digital twins for predictive combustion modeling. The research program will cover a wide range of e-fuels (H₂, NH₃, CH₃OH, DME, OME) and their
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are particularly interested in candidates who combine computational biology, data science, and machine learning/AI with deep biological insight. While wet lab activities are welcome, they are not mandatory. However
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required. • Programming skills are required. • Knowledge of Natural Language Processing and Machine Learning is preferred. • Fluent English required, both oral and written. French is appreciated but
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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | about 1 month ago
access to GRAME-CNCM (computer music center based in Lyon) facilities, fostering potential collaborations with artists, etc. References [1] Gregorio Giudici, Franco Caspe, Leonardo Gabrielli, Stefano
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-supervision by a doctor and a statistical/machine-learning researcher is planned (iBV / Inria) 1- Context and Objective: Monitoring tumor response using clinical imaging, such as CT or FDG-PET, has become a
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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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advances in machine learning and data-intensive approaches facilitate the search for better or even global minima via evolutionary computations or reinforcement learning. Objectives. The main scientific
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centre at Universit´e Cˆote d’Azur, I3S Lab (Universit´e Cˆote d’Azur and CNRS) in collaboration with the Machine Learning Genoa Centre (MaLGa) at the University of Genova (Italy). The candidate will be