Sort by
Refine Your Search
-
join a multidisciplinary research team at the interface between physics, engineering, and clinical research, including scientists, engineers, physicians, and PhD students. The position involves close
-
Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Deep learning models, and in particular large language
-
, the web AI, and politics. For this position, we seek to develop the análisis of web and social media data using AI methods, as well as investigating AI models themselves. We are looking for candidates with
-
26 Oct 2025 Job Information Organisation/Company CNRS Department Astrophysique, Instrumentation, Modélisation Research Field Astronomy Astronomy » Astrophysics Astronomy » Cosmology Researcher
-
FieldEconomicsEducation LevelPhD or equivalent LanguagesFRENCHLevelBasic Research FieldEconomicsYears of Research ExperienceNone Additional Information Eligibility criteria PhD on the economic modelling of the oil market
-
ExperienceNone Additional Information Eligibility criteria - PhD in theoretical chemistry or theoretical physics, with experience in methodological developments is a plus. - Solid knowledge in electronic structure
-
FieldPhysicsYears of Research ExperienceNone Additional Information Eligibility criteria The candidate should hold a PhD in reactor physics or an equivalent degree. He or she should: - Have a good understanding of
-
shall also contribute to activities such as • Supervising a PhD student in the group, • publication of two or more individual and/or joint articles on the analyses of the data collected during the project
-
), whose objective is to extend the HLA-Epicheck model, originally developed within the framework of a PhD thesis, and to implement new deep learning approaches to assess donor–recipient compatibility in
-
approaches to model polarization. The aim of the project is to develop methodological tools to characterize and exploit the polarization information extracted from bivariate signals (i.e. two-dimensional