Sort by
Refine Your Search
-
Listed
-
Employer
- CNRS
- Institut Pasteur
- French National Institute for Health Research (INSERM)
- Universite de Montpellier
- University of Luxembourg
- DI ENS
- ESSEC Business School
- INSERM DR Paris 5
- La Rochelle Université
- Luxembourg Institute of Health (LIH)
- Luxembourg Institute of Science and Technology (LIST)
- University of Caen Normandie
- University of Lille
- Université Côte d'Azur
- Université Savoie Mont Blanc
- Université de Bordeaux / University of Bordeaux
- Université de Caen Normandie
- 7 more »
- « less
-
Field
-
, colloquia, and summer schools. Your profile PhD in Theoretical Physics Excellent analytical and numerical skills Solid knowledge of Statistical Physics Proficient in English (C1) We offer A modern, dynamic
-
models, large language models, and statistical mechanics to conduct research in the following areas: (1) Development of data-driven schemes for the discovery of slow variables. (2) Molecular simulations
-
for advanced statistical and time-series analyses. They will analyse behavioral, EEG and eye-tracking data collected during prolonged experimental sessions. The research will focus on the modelling and
-
on astrophysical source populations and dark-matter signals, exploiting statistical correlations across datasets to break degeneracies that limit single-probe analyses. The framework will be validated on synthetic
-
. - Applied Mathematics and Statistics: Knowledge of statistical methods and algorithms for data analysis, including model fitting, regression, and sensitivity analysis. Expertise - Scientific Collaboration
-
26 Aug 2026 Job Information Organisation/Company University of Lille Research Field Chemistry » Computational chemistry Physics » Statistical physics Chemistry » Physical chemistry Physics
-
of aerosol chemical composition profiles. These methodologies will be extended to monitor stratospheric sulfate aerosols within the framework of the ESA STATISTICS and STATISTICS-II projects. The successful
-
, integrating statistical inference, machine learning, and population genetics. We will develop advanced computational methods to characterize the functioning of T- and B-cell repertoires. The goal is to build
-
. Unsupervised machine learning approaches will be used to identifiy key dimensions of circadian rhythm associated with dementia subtypes. This requires a very good level in statistics and R programing as
-
hold a PhD in the fields of ecology or evolutionary biology, or biostatistics/biomathematics. Required skills: - Data analysis using R and database management - Statistical modelling for ecology