Sort by
Refine Your Search
-
cells developed in our group. References: [1] C. J. Traverse, R. Pandey, M. C. Barr, R. R. Lunt, Nat. Energy, 2017, 2, 849–860. [2] (a) W. Naim, V. Novelli, I. Nikolinakos, N. Barbero, I. Dzeba, F
-
inorganic carbon. Global Biogeochemical Cycles, 36, e2021GB007162. https://doi.org/10.1029/2021GB007162 van der Zant, H. F., Sulpis, O., Middelburg, J. J., Humphreys, M. P., Savelli, R., Carroll, D
-
, - Proficiency in R and/or Python programming languages, - Experience working with large medical-administrative databases would be appreciated (SNDS, PMSI), - Excellent command of scientific English (written and
-
, parsimony, total-evidence approaches). Candidates must have expertise in macroevolutionary modeling tools (BAMM, PyRate, FBDD, BDNN, DeepDive). Strong programming and quantitative skills (e.g. R). Experience
-
knowledge of basic techniques in molecular biology. Working knowledge of R and Python programming environments. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR5284-FABLEG-002
-
an asset for the position (Da Rocha et al., 2025a). Bibliography: A Baldit, M Dubus, J Sergheraert, H Kerdjoudj, C Mauprivez, and R Rahouadj. Biomechanical tensile behavior of human wharton's jelly. Journal
-
. He/she will need to master data processing software such as R. The candidate is also expected to be curious and imaginative, to challenge the team by proposing radically different approaches
-
quantitative geoscientific data. • Experience with one programming languages e.g. Python, Matlab, R. Critères essentiels : - Être titulaire d'un doctorat en géomorphologie ou dans une discipline étroitement liée
-
Technical skills : - Ability to handle large datasets (hundred thousands to millions of rows) using a programming language (e.g. R, Python, MATLAB) - Good knowledge of descriptive multivariate data analyses
-
appreciated. - Advanced statistical modeling (GLMMs, state-space models, stochastic Bayesian programming) in R - Experience with bioinformatics, if possible experience in the use of RAD-seq and/or lcWGS data