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on the statistical analysis for multiple projects involving large scale databases from various cohorts, including but not limited to traumatic or hypoxic brain injury, spinal cord injury, Alzheimer’s disease and
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data, and we work at the interface of epidemiology, social sciences, statistics, bioinformatics, and genetics. Housed within the Faculty of Medicine, the School of Population and Public Health (SPPH) is
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state of the art data science and statistical approaches in the context of emerging frameworks for detecting and attributing biodiversity change. Sentinel Postdoctoral researchers will be co-advised by
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McCreary Centre Society Other activities as required Job Qualifications: Completed a Ph.D. within the last 5 years (or shortly expect to complete) in a relevant discipline (e.g. public health, statistics
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handling multi-dimensional biological datasets. Candidates with skillsets and experience in managing large genomes and statistical genetics will be preferable as well. The successful candidate will have: - A
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statistical genetics will be preferable as well. The successful candidate will have: - A PhD in Bioinformatics, Computational Genetics, or related fields - Experience with handling large data, scripting and
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and Public Health, Psychology, or similar area of study). Strong expertise in the design, implementation, and analysis of mixed methods study designs. In-depth knowledge of fundamental statistical
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expertise in the design, implementation, and analysis of mixed methods study designs. In-depth knowledge of fundamental statistical concepts, methods, and techniques and experience with quantitative
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designs. In-depth knowledge of fundamental statistical concepts, methods, and techniques and experience with quantitative statistical analysis software (SPSS, STATA, SAS or R). Familiarity with randomized
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themes of the laboratory’s interests. Minimum Qualifications: Doctorate in computational biology, bioinformatics, computer science, statistics, genomics/genetics or a related field. Proven computational