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technology. Moreover, the close connection with the clinical environment allows for translation of novel methods to our cancer clinics in Canada (Vancouver, Victoria, and Kelowna) and beyond. RESPONSIBILITIES
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) at McGill University is accepting applications for a post-doctoral researcher position in human sport performance. The intent of this program is to support research that aims to understand, facilitate, and/or
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projects. The nature of the work demands planning the sequence of duties and work methods in consultation with the LOA Manager. The Archaeology Collections Research Assistant must exercise good judgement
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. Qualifications: A doctoral degree in epidemiology Knowledge of advanced epidemiologic methods Strong data manipulation and analytic skills using statistical programming software, e.g., SAS Demonstrated ability
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to prevent pediatric mortality and morbidity, enabled through digital health technologies in Africa (Kenya, Uganda + more). The Trainee will be working on a program with over 15+ years (Smart Discharges
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(LAFOV) PET/CT scanner, and aims to push the limits of modern technology. Moreover, the close connection with the clinical environment allows for translation of novel methods to our cancer clinics in
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methods for investigators with novel research projects. The incumbent is expected to keep abreast of techniques and developments in their area of expertise. Exceptional organizational skills, as well as a
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/deep learning methods for biochemical applications to work in a multi-disciplinary team. The applicant will work with a team of biochemists, computational chemists, and pharmacologists and contribute
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Dalhousie University | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | 26 days ago
. Eric Rapaport and his team are now seeking applications for a two-year Postdoctoral Fellowship in a research program called A data-driven geospatial planning tool: understanding cumulative climate risks
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Council of Canada). The research will focus on applying, developing, and implementing novel statistical methods for causal inference, integrative data analysis, and machine learning with large