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simulations, machine-learned force fields, and artificial intelligence (AI). The successful candidate will lead the development of a computational platform that unifies first-principles methods, classical
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Mattelaer, Christophe Ringeval). Research activities in include SM and BSM aspects of collider physics (LHC and future colliders, simulation tools, machine learning, effective field theories, amplitude
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skills and experience: Essential criteria PhD or equivalent (or thesis submitted*) in at least one of the following subjects: Computer Science, Machine Learning, Biomedical Engineering, Medical Imaging
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biological environments - Experience using machine‑learning algorithms for luminescence signal analysis and sensing applications - Experience writing scientific articles and presenting results at conferences
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support the research enterprise in computational biology, biophysics and machine learning activities. The research associate will work with Dr. Morcos to tackle computational problems in the area of
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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | 30 days ago
, curious, autonomous, proactive and dynamic. A specialization in optimization, machine learning, statistical learning or game theory is appreciated. Research experience is a plus. LanguagesFRENCHLevelBasic
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tools in research. Excellent written and oral communication skills, with a proven track record of publishing scientific papers and delivering presentations. Experience with machine learning techniques
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or information and communication technology, 2) experience in teaching, 3) experience in machine learning, deep learning, particularly in the application of biomedical data processing, 4) experience in processing
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are looking for a motivated postdoc with solid experience in bioinformatics and in machine learning. The position centers on SRPs and LLPS, and the successful candidate will contribute to several ongoing
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: 10.1101/2025.09.08.674950), and AI/machine learning. We work closely with clinicians to translate our findings into clinical practice, focusing on genomically complex sarcomas and haematological