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Nature Careers | Vancouver South Shaughnessy NW Oakridge NE Kerrisdale SE Arbutus Ridge, British Columbia | Canada | about 10 hours ago
information on patients. The group’s homepage: https://www.skane.se/en/about-us/research/for-dig-som-forskar/center-for-primary-health-care-research/molecular-family-medicine-laboratory/ https
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LanguagesENGLISHLevelExcellent Additional Information Website for additional job details https://www.postdocs.ubc.ca/ad/58986 Work Location(s) Number of offers available1Company/InstituteThe University of British Columbia (UBC
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: PhD in physiology or related discipline and Quercus experience are required. Lecturing experience in physiology and in teaching large classes are also required. Previous teaching experience in PSL301H
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Unit 3 Collective Agreement, the rate of pay for teaching in this course will be $4,200, inclusive of vacation pay. Qualifications: PhD in physiology or related discipline and Quercus experience
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: Design and implement ML, deep learning, and Large Language Models for orthopaedic applications Work with multimodal clinical data, including: Medical imaging (X-ray, CT, MRI) Electronic health records (HER
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deadlines. Skills: Background in horticulture, plant genomics, large-scale data analysis, or programming skills is preferred. Demonstrated experience in population genetics using genome-wide genetic marker
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of British Columbia in Vancouver, Canada, invites applicants for a full-time, PhD-level research associate in Evolutionary and Quantitative Genomics. Reporting to Dr. Judith Mank, the applicant will have
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Laboratories (at London Health Sciences Center). More information on facilities can be obtained at:https://www.schulich.uwo.ca/research/research_excellence/core_facilities.html and https://lawsonimaging.ca
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). RESPONSIBILITIES Reporting to Dr. Eva Oberle, Associate Professor, the incumbent will be responsible for: Conduct quantitative research using population-based and large-scale data on child health and wellbeing
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junior research team members (including undergraduate research trainees). Qualifications ● PhD in computer science, bioinformatics, data science or similar, with a focus on machine learning