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Field
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hydrological modeling at catchment scale, and familiarity with modeling tools. Proficient in statistical analysis and programming languages such as Python, R, or MATLAB. Strong written and verbal communication
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the use of bioinformatics tools for metagenomic and transcriptomic data analysis (e.g., QIIME, DADA2, R, Python). Demonstrated ability to independently design and conduct experiments, analyze data, and
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to contribute to the development of a regional, high-resolution (80 m) configuration of the global ECCO-Darwin model (Carroll et al., 2020; www.ecco-group.org ; https://darwinproject.mit.edu ). The selected
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-level optimisation using TRNSYS and MATLAB/Python. The associate will use advanced characterisation (e.g., DVS, porosimeter, DSC/LFA) to develop and assess adsorption composites, and apply CFD to analyse
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manufacturing. It is meritorious to have previous experience in data analysis and processing with Python (or similar), preferably including documented experience with machine learning tools. It is meritorious
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in the use of geometric or morphological methods (e.g., Voronoi analyses, clustering methods, Minkowski functionals) Very good programming skills (e.g., in Python, C++, or comparable languages
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programming skills (e.g., Python) Previous experience with analyzing sequencing data Excellent communication abilities, and a collaborative mindset Meritorious for the position: Demonstrated work on developing
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polarimetry for the metrology in microelectronics, studies of nanomaterials, and optical diagnosis of various biological tissue including plants. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre
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in grant development (including methodological proof-of-concept work) and in writing first-author publications in high-impact journals. Where to apply Website https://www.academictransfer.com/en/jobs
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experience in quantitative methods, including automated content analyses and/or handling panel data Advanced analytical skills preferably using in R, Stata, or Python Excellent proficiency in English What do