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health tools. Basic proficiency in data analysis (Python or R); experience with speech analysis libraries or NLP is an asset. Strong scientific writing skills and a collaborative spirit. High motivation
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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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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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, 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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: Programming in Python and/or R Data science (e.g., tidyverse, pandas) Machine learning (e.g., scikit-learn) Deep learning (e.g., PyTorch, Keras3) (Optional) bio-signal processing and brain imaging (e.g., EEG