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. • Knowledge of liquid–liquid extraction processes would be a strong asset. Soft skills: • Experimental rigor and critical analysis skills. • Autonomy, scientific creativity, and a sense of innovation. • Good
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conditions. Profile: Required degree: Master's (M2) in Ecology and Evolution - Specialization: Modeling in ecology and evolution, theoretical ecology Expected skills: - Statistical analysis - Mathematical and
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will be responsible for performing a sensitivity analysis of SDM modelling applying for five gorgonian species applying BIOMOD2 to the same data set as the one used in Blouet et al. (2024) and extend
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-Induced Phosphorescence (LIP) Additional diagnostics—potentially in collaboration with TUD—or complementary numerical simulations may be used to support the physical analysis of the turbulent flame
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problem caused by unidirectional replication initiation in the proliferation arrest induced by DciA depletion. The thesis work will be divided into two parts: (i) analysis of the consequences of DciA
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accelerator physics • Python (or C++, Fortran) coding • analytical skills • basis of data analysis • a high level of communication skills, both oral and written (French and English required) to be able
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(especially fMRI), experimental design, data analysis and programming (e.g., SPM, MATLAB, Python, R,…), scientific writing, and very good organization and communication skills. The ideal candidate is able
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and transcriptomic data that will be subjected to bioinformatic analysis to integrate and interpret complex datasets, helping us to better understand the underlying mechanisms of the disease. Our
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activities: - This research is based on a detailed analysis of atmospheric measurements from a multi-sensor network (remote sensing and surface stations) using statistical analysis and a physical understanding
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equipment, particularly in imaging and electron microscopy, image analysis, and bioinformatics. The team is composed of five people. The thesis will be carried out as part of a collaborative ANR project