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experience working with cohort data or electronic health records is an asset; Interest in digital health and diabetes research; Proficiency in R and/or Python; Excellent writing and communication skills in
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, computational neuroscience, or a related field Strong programming skills in at least one of the following: Python, R, MATLAB, C, or C++ Demonstrated experience in statistical analysis and/or machine learning
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data generated by PEPR project collaborators. This includes: Developing a reproducible analysis approach implemented in R. Interacting directly with project collaborators based in Lyon (mainly remotely
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and very good knowledge in quantitative and qualitative research methods Good knowledge of statistical software (e.g. SPSS or STATA or R or JASP) Strong commitment and the ability to work in a team
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on datasets (previous experience in SPSS, STATA, or R is an advantage); Experience in using literature reference management software tools including Endnote; Good writing skills in English. The understanding
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to learn: R, python, Java, web services, Docker containers and UI design Git-based subversion control (GitHub, GitLab) Non-target workflows for mass spectrometry data Major cheminformatics toolkits (e.g. CDK
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. Klingner and J. R. Shewchuk, “Aggressive tetrahedral mesh improvement,” 2008, doi: 10.1007/978-3-540-75103-8_1.
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, including the development and use of 3D models and the study of extracellular vesicles Analyze high-throughput data sets using R or similar software Present research findings in meetings Document performed
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SLICES-FR research infrastructure- Communicate results through presentations, conference papers, and project reportsProfile and skillsThe R&D Engineer must already hold a PhD degree in Computer
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proficient in programming languages commonly used in genomics research (e.g. Python or R) and have experience in working with bioinformatics software. Good knowledge of English is necessary. The successful