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at the University. This is a part-time 10% FTE. At UBC, we believe that attracting and sustaining a diverse workforce is key to the successful pursuit of excellence in research, innovation, and learning for all
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selected as one of Canada’s Best Diversity Employers and a Greater Toronto’s Top Employer for 2015, 2016, 2017 and 2018. To learn more about our work environment, colleagues, leaders, students and innovative
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selected as one of Canada’s Best Diversity Employers and a Greater Toronto’s Top Employer for 2015, 2016, 2017 and 2018. To learn more about our work environment, colleagues, leaders, students and innovative
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Position Summary: Proposed project title: “Targeted & Non-targeted analysis of PFAS in food packaging“. Develop and apply liquid chromatography (LC) methods coupled with high-resolution mass spectrometry
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research, innovation, and learning for all faculty, staff and students. Our commitment to employment equity helps achieve inclusion and fairness, brings rich diversity to UBC as a workplace, and creates the
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Nature Careers | Vancouver South Shaughnessy NW Oakridge NE Kerrisdale SE Arbutus Ridge, British Columbia | Canada | 3 months ago
. For those interested, there is also an option to learn and use in vivo cancer or diabetes models. Collaborative and Supportive Environment: You will collaborate closely with experienced scientists and
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first author publications in reputable peer-reviewed journals Advanced quantitative skills (e.g., advanced stats [MLM], machine learning, data mining). Willingness to develop desired skills (see directly
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group, founded in 2021, is dedicated to advancing our understanding of the neuronal mechanisms of learning and decision-making. We are particularly excited to recruit a promising scientist to investigate
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Qualifications: Expertise in C. elegans husbandry, genetics and experimental manipulation - Expertise in florescence microscopy, particularly confocal and live-cell imaging - Expertise in image analysis, including
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are not limited to superconducting quantum circuits, circuit QED, quantum error correction, microwave quantum optics, variational quantum algorithms, and the application of machine learning to quantum