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environmental data Processing and analyzing large-scale remote sensing datasets from UAV, satellite, and ground-based sensors Leveraging artificial intelligence, e.g. machine learning, reinforcement learning
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youth populations. The analysis will require advanced complex sample statistical data analyses of two large population-based health surveys: the BC British Columbia Adolescent Health Survey and the Health
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writing. Responsibilities will include: Conduct advanced multivariable statistical analyses of large-scale population-based data using SPSS Complex Samples and Mplus Draft and lead the submission process
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hydrogen/methane blends in 15 MW boilers and prepare a report (thermal power and heat transfer analysis at large-scale); b) Collaborate with UBC technicians in acquiring data from our 15 MW boilers, analyze
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Bison Integrated Genomics and Assisted Reproductive Technologies for Germplasm Biobanking (BIG ART) Primary Purpose: Bison are an integral part of the ecology of Canadian national parks. Parks
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been recent rise in vision foundation models such as GPT-4o, Instruct-BLIP and LLava. However, training foundation models has significant environmental costs tied to large scale datasets as highlighted
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embrace the complexity of digital health implementation and data-driven predictive modelling in low-resource settings with passion, resilience, and lots of creativity. Find yourself in new areas of inquiry
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statistics, data management). Comfort handling large and diverse datasets. Strong coding skills (R and/or Python), with experience using a high-performance computing platform (e.g., Digital Research Alliance
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, or data analysis is highly desirable and would be considered a valuable asset. Additional skills that would strengthen a candidate’s application include: experience with whole-genome or exome sequencing
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, or data analysis is highly desirable and would be considered a valuable asset. Additional skills that would strengthen a candidate’s application include: experience with whole-genome or exome sequencing