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enhance provincial capacity to tailor care approaches in response to the ongoing substance use crisis. The ideal candidate will have a passion for integrating multiple sources of quantitative data and a
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to the ongoing substance use crisis. The ideal candidate will have a passion for integrating multiple sources of quantitative data and a drive to explore new areas of inquiry critical to transforming the quality
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provides accurate, high throughput data, ideal for identifying single nucleotide variants, expression profiling, and performing bulk analyses. These and related technologies are positioned to transform our
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with strong background in Computer Vision and Machine Learning. Position Overview: In this position, you will investigate the existing solutions for assessing datasets and developing a novel tool relying
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increasing disturbances, such as wildfire and climate change. By integrating field research, remote sensing, and operational forestry insights, this project will generate data-driven tools and practical
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partners. Minimum Qualifications A PhD in Forestry, Environmental Science, Ecology, or related fields. Strong expertise in forest carbon accounting, including carbon stock quantification. Proven experience
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of data, creating diverse training opportunities. Interested applicants should have a PhD in biology, molecular biology, biomedical engineering, biotechnology, materials science, computer
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contribute to research outputs, stakeholder engagement, and project coordination in close collaboration with the project PI and international partners. Minimum Qualifications A PhD in Forestry, Environmental
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Professor Gunilla Öberg (recent settler from Sweden), University of British Columbia. More information on the larger project can be found here and here . The successful candidate will work under the
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Qualifications A PhD in Forestry, Environmental Science, Ecology, or related fields. Strong expertise in forest carbon accounting, including carbon stock quantification. Proven experience in biodiversity