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with 3D cell culture, organoids or tissue engineering will be considered a strong advantage. Experience with image analysis software (ImageJ/Fiji) and scientific computing tools (Python, R or equivalent
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analyze multi-omic data provided by our collaborative partners and interpret the results from a biologically relevant perspective. Planned activities include Python code development, the analysis and
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bacterial genome analysis and comparative genomics. * Skills in bioinformatics applied to genomic data analysis. * Experience in data analysis and visualization, particularly using R and/or Python. * Ability
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Eligibility criteria Selection will be based on the following scientific and technical criteria: • PhD in computational biology, machine learning, bioinformatics or a related field. • Proficiency with Python
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- 4 Additional Information Eligibility criteria - Evolutionary genomics analyses on large NGS datasets -Knowledge on coding (C ,C++, or java), script writing (python, perl), R software and shell Unix
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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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, 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
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, K-means clustering, random forest trees, hypothesis testing, etc.) - Python programming and the Unix environment - Ability to communicate results in French and English (writing scientific articles and