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Field
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of sea turtles - Developing innovative machine learning methods to analyze the sounds associated with these behaviors - Automating the processing of audio and visual data to optimize the quantity and
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relevant, in vivo. - Data Analysis and Dissemination (analysis and interpretation of experimental data, preparation of manuscripts, contribution to grant writing and progress reporting). - Collaboration with
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Science, or Information Science. The position requires experience with at least one of the following: Data Science, Machine Learning, Computational Social Science, Big Data. Relevant skills could include statistical analysis, data
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in spatial analysis & GIS and remote sensing for land/water/agricultural applications. Strong programming skills in Python and/or R (geospatial stacks, data wrangling, visualization). Record of peer
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5 Feb 2026 Job Information Organisation/Company Université de Limoges Department DRH-RECHERCHE Research Field Educational sciences Literature Cultural studies Researcher Profile First Stage
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experience: behavioral and/or molecular neuroscience; or bioinformatics; Skills: brain surgery and behavioral tests on rodents, or advanced image and data analysis; Experience in iDISCO brain clearing, light
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, including induced pluripotent stem cell (iPSC)-derived cells. Knowledge of advanced bioinformatics tools for DNA/RNA sequencing data analysis, functional annotation, and data visualization (preferred
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, vehicle dynamics, and complex real-world environments. Research themes include model predictive control, reinforcement learning, reachability analysis, uncertainty quantification, and safety-critical visual
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analytical and modeling skills, including data science, database management, data visualization, etc. Strong publication record Experience working on subjects related to one or more of three main research
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/bioinformatics, and data science. Work Performed · Work in highly collaborative inter-disciplinary environment with clinicians, econometricians, statisticians, and data scientists · Lead statistical analysis