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. Experience in conducting experimental work (experimental internship) 2. Basic understanding of magnetohydrodynamics 3. Knowledge of Python programming 4. Experience in signal and/or image processing _Personal
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-based and/or learning-based motion generation for robots (particularly aerial drones). - Development: Proven experience and proficiency in C++ and Python. - Specific Knowledge: Prior knowledge of event
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field) and ground-based (radio) data - Use of various software codes: (i) radio emission simulation code, (ii) solar wind propagation code. - Development of software (preferably in Python) for data
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(interactive phylogenetic trees, Sankey diagrams). Report generation and statistical analysis • Statistical analysis of viral abundances (Wilcoxon, ANOVA), regression models (R, Python: statsmodels, scikit-learn
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analysis. - Adapt the team's existing data analysis protocols as needed. Expertise in coding (Python, ImageJ) would be a plus. - Be able to communicate research results, whether within the team
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languages commonly used in the scientific environment (especially R, Python) would be an asset. Most of the work will be carried out in the laboratory at the LAPA facilities on the CEA Saclay site. Field
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in Python and/or C++ programming will be considered a strong advantage. Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UMR7315-DAMAND-006/Default.aspx Requirements Research
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, ideally molecular dynamics and/or DFT. Scientific programming skills, particularly in Python, are expected. Familiarity with machine learning or generative AI methods applied to materials would be a strong
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programming skills (Python, Fortran, …); • Excellent communication skills, with the ability to work in an international research environment and publish scientific results in English; • Experience in retrieving
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, acceleration, algorithms for optimal transport or generative AI). A good knowledge of Python programming (for AI, optimization) is highly desirable. Website for additional job details https://emploi.cnrs.fr