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collaborative, working closely with other research labs on large scale projects. Sources of data include large-scale datasets (All of Us, UK Biobank), internal BC-based projects (eg., Silent Genomes; Rare
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analyses and modeling of large planetary data sets including visible and near-infrared imagery, synthetic aperture radar imagery, radar altimetry and LiDAR. The selected candidate will collaborate with
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to contribute to and expand research in planetary science in the Department of Earth, Ocean & Atmospheric Science. The position will involve quantitative analyses and modeling of large planetary data sets
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in selecting and interpreting information from the CUPE 2278 collective agreement to oversee and manage a large staffing base of CUPE 2278 members. Exam Coordinators may also invigilate exams
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of expertise. QUALIFICATIONS BSc or MSc in a Data Science. Minimum 3 years of related experience or the equivalent combination of education and experience. Expertise in large biological databases, specifically
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infrastructure awards. Errors and poor decisions by this position could result in unreliable information or no information being available to effectively manage the finances of a large and very complex grant
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of the financial information workflow, enhances management of financial resources and ensures integrity of financial transactions in a large, complex department. Compiles financial transaction documents and delivers
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analyze large volumes of complex information. Experience in managing caseloads and meeting deadlines in a high-volume service environment. Ability to quickly learn new technologies and systems. Proficiency
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procedures (e.g., multilevel modeling, longitudinal data analysis, machine learning algorithms), cleaning and structuring large datasets, validating model assumptions, and ensuring reproducibility. Synthesizes
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whole genome sequence data generated at an approved genome centre, the implementation of quality control analyses, the construction of the database to host the generated genetic data and the