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correlated electron systems Proficiency with scripting or programmatic languages, such as Python, c, and matlab Excellent written and oral communication skills. Motivated self-starter with the ability to work
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research, with proficiency in research software appropriate to the candidate’s methodological expertise (e.g., R, Python, SPSS, NVivo, or MAXQDA). Experience designing, deploying, or evaluating generative AI
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related field Experience with genome assembly and/or large genomic datasets Strong computational skills (Unix/Linux, scripting in R/Python) Publication record in peer-reviewed journals Other Position
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related field. Demonstrated expertise in multi-omics integration and large-scale data analysis. Strong programming skills (e.g., R, Python, workflow systems). Proven publication record in peer-reviewed
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related field. They should demonstrate: Strong programming skills in Python and R. Experience developing bioinformatics analysis pipelines for spatial (or single cell) omics data and / or experience
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in one of the following areas: Machine Learning / Information Retrieval / Knowledge Graph Representation / Recommender Systems Graph Theory/Network Science Python, and up-to-date machine learning
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the McGill BioPortal. Develop and maintain reproducible analysis pipelines in R, Python, and shell on HPC / Slurm clusters and cloud environments (e.g., DNAnexus, Terra, AWS/GCP). Write first-author
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FieldEconomicsEducation LevelPhD or equivalent Skills/Qualifications PhD in Physics, Applied Mathematics, Economics/Econophysics, or a related quantitative discipline. Strong programming skills in Python for scientific
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techniques; large data processing and high performance computing; advanced causal inference and statistics; computer vision and novel applications of machine learning. Advanced knowledge of R or Python is
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computing, or computational fluid dynamics. Programming experience, preferably in Python, C++, and/or MATLAB. Ability to work both independently and collaboratively. Excellent analytical and problem-solving