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our institution: https://liubapapeo.wordpress.com/ https://sites.google.com/site/jrhochmann/ https://babylablyon.fr/ https://www.isc.cnrs.fr/en/homepage/ https://www.cnrs.fr/fr Where to apply Website
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, GC-MS/MS, and advanced NMR approaches. - **Activity 4:** Multivariate statistics and machine learning to identify microbial and chemical biomarkers of resilience and reveal the interactions linking
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at the Laboratory for Biometry and Evolutionary Biology (LBBE) in Lyon, France (https://lbbe.univ-lyon1.fr/en ). The LBBE comprises approximately 200 people; the research conducted there is based on three pillars: (i
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
., Revenko, A., Teije, A. T., & Harmelen, F. V. (2023). Combining Machine Learning and Semantic Web: A Systematic Mapping Study. https://doi.org/10.1145/3586163 [2] Benoît Combemale, Pascale Vicat-Blanc
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). The available thesis projects are listed here: https://adum.fr/as/ed/proposition_Setab.pl APPLICATION PROCESS Applications must be submitted via the BEST application portal Deadline for applications : 23 November
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Website https://emploi.cnrs.fr/Offres/Doctorant/UMR8180-CLEGHI-002/Default.aspx Requirements Research FieldChemistryEducation LevelMaster Degree or equivalent Research FieldEnvironmental scienceEducation
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Inria, the French national research institute for the digital sciences | Saclay, le de France | France | 2 months ago
/hal-04213978 Pierre Cesar, Sofya Dymchenko, Abhishek Purandare, Bruno Raffin. *Learning Where to Simulate: Generative Active Sampling for Online PDE Surrogate Training*. 2026. https://inria.hal.science
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nanomaterials would be particularly appreciated. An interest in interdisciplinary approaches at the interface of chemistry, nanoscience, and biology is also highly desirable. Where to apply Website https
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, or computer science. Core competencies: solid background in quantum many-body physics strong programming skills (Python required, Rust a plus) experience with tensor networks, variational Monte-Carlo, machine learning
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to correlate polymerisation kinetics, macromolecular architecture, morphological evolution and drug encapsulation mechanisms. Beyond experimental work, the project will integrate machine learning approaches