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Field
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researchers and graduate students. Required Knowledge, Skills and Abilities AI/ML Expertise: Strong knowledge of advanced machine learning, deep learning, and AI techniques. Programming Skills: Proficiency in
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quantitative data analysis: applied machine learning, statistical analysis, and handling complex data. Programming skills in Python and R are essential Experience in applying computational methods to research
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area of expertise. You may be a great fit if: You are a passionate researcher with a PhD in Computer Science or a related field, experienced in machine learning for spatial data management, with a track
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information, disability, age, ancestry, military service, protected veteran status, or other characteristics protected by law.
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have exceptional resources to facilitate research including access to administrative, research, and computer support staff. Required Qualifications* PhD degree or equivalent in epidemiology, gerontology
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transportation operations and network modelling, accessibility analysis, data analysis (statistics and/or machine learning methods), and spatial mapping. Because the work will involve multiple years of daily
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informatics approaches (e.g., machine learning, Bayesian statistics) and spatial data processing and analysis skills would be of advantage. Expertise in Stata, R, or other analytic tools. Strong communication
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of analyzing large-scale population data. Experiences working with electronic health records (desirable). Understanding of clinical informatics approaches (e.g., machine learning, Bayesian statistics) and
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the following training will be considered PhD in computer science, machine learning, AI or related computational field, or, Ph.D. in a health-related discipline with experience in experimental science, devices
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-performance computing, machine learning models (eg. LLM), probabilistic models for data, novel techniques for making measurements, visualization tools, and community-oriented foundational software tools. Please