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biostatistics and epidemiology Expertise in quasi-experimental, econometric methods and other advanced methods (e.g., longitudinal data analysis, trial emulation, interrupted time series, machine learning
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Government of Canada | Government of Canada Ottawa and Gatineau offices, Ontario | Canada | about 1 month ago
through a research program in foundational mathematics and computer science, with concentrations in cryptology and machine learning research. Job Summary TIMC is seeking highly qualified researchers
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in artificial intelligence (AI) and/or machine learning. · Ability to support grant applications and ongoing research project development as well as prepare manuscripts, policy briefs, technical
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research in cardiovascular and autonomic (i.e., bowel, bladder, sexual and cardiovascular) dysfunctions following SCI Demonstrated expertise in current machine learning techniques applied to biological
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). The candidate will be working on developing state-of-the-art methodology in clinical prediction modeling, including novel uncertainty assessment method (Value of Information analysis), as well as Machine Learning
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monitoring. Familiarity with computational image analysis, scripting (Python, MATLAB), or machine learning–based image workflows. Experience with method development, imaging assay optimization, or pipeline
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(3) years in a relevant field (e.g., Computer Science, Computational Linguistics, Data Science or related disciplines) Strong experience or demonstrated interest in AI, NLP, machine learning
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applicants will have: PhD in epidemiology and/or biostatistics, public health or related field Demonstrated expertise in epidemiologic study design, vaccine effectiveness evaluation, and/or infectious disease
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PhD (or equivalent) in Machine Learning, Computer Science/Engineering, Biomedical Engineering, or PhD or equivalent degree in population/public health and other related medical fields with AI and ML
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disciplines) Strong experience or demonstrated interest in AI, NLP, machine learning, or digital health research Experience working with clinical, communication, or patient-generated datasets is an asset