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) · Knowledge of heat transfer and multiphase systems · Scientific programming skills (C/C++, Python, or Fortran) · Experience with advanced numerical methods (LBMor similar) · Familiarity with HPC
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for electrophysiology, imaging, and behavioral data analysis using Python, MATLAB, ImageJ/FIJI, DeepLabCut, or related tools. Maintains accurate records of experimentation, animal procedures, data analysis, and research
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relevant discipline, e.g., environmental statistics, environmental economics, ecology, etc., and demonstrated strength in applied data science with environmental applications. Expertise in R and Python
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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
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physiology, forestry, geography) Background in data intensive processing and analysis using open-source code (e.g., Python, R) Demonstrated proficiency in code documentation and reproducibility, and
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field Strong quantitative and statistical skills, with proficiency in R or Python Experience analyzing longitudinal, infectious disease, clinical, or high-dimensional data Demonstrated record of peer
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biological field. You must possess documented experience managing spatial/scRNA transcriptomics workflows. Strong programming proficiency in R or Python is essential. Proven experience in data acquisition
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-seq Hi-C Micro-C RCMC Organoid culture systems Mouse models Flow cytometry DNA damage and repair assays Computational genomics and bioinformatics Programming and analytical tools such as: R Python
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programming skills in Python, R, or similar languages. Experience working with large biological datasets. Familiarity with Linux-based computing environments and high-performance computing. Excellent analytical
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research and scientific publications Teaching experience at BSc and/or MSc level Strong quantitative skills — ecological data analysis and reproducible workflows in R and/or Python Fluency in English Desired