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interest in historical research, migration, and digital infrastructures Familiarity with digital tools and languages such as Wikibase, SPARQL, RDF, Python, GitHub, and Jupyter Notebooks is highly desirable
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skills : We expect a candidate with a strong background in machine learning or statistics. The candidate must also be proficient in high-level languages like Python. Familiarity with single-cell date and
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qualifications: Masters degree in cognitive science, vision science, neuroscience, or related fields Programming skills (Python, MATLAB) Good communication skills in English Experience with experimental data
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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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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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: 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