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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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Artificial Intelligence (AI), particularly in the development and application of Large Language Models (LLMs), to join our team working on predictive maintenance solutions. The ideal candidate will have
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taxonomy in AI-assisted workflows Prototype and test automated classification scripts (Python/R) Document data pipelines and QA/QC procedures Supervision & Training Mentor PhD-level and undergraduate RAs
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demonstrated independent thinking and problem-solving abilities. Experience using large databases is preferred, and genetic data analysis skills are desirable. Required Qualifications PhD or MD in Public Health
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and reduction of very large data sets, data analysis, and simulations of X-ray scattering and spectroscopy signatures of dynamic processes in battery materials. The theoretical/ simulation efforts
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About the Role You will develop and apply novel computational methods to quantify the societal impact of fundamental science discoveries. Candidates close to completion of their PhD will initially
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the Project HOPE 1000 pregnancy cohort, a large, longitudinal study based in Durham, North Carolina, to investigate how prenatal and early-life environmental exposures influence immune-related outcomes during
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interpretation of atmospheric circulation in high-resolution reanalysis data, idealised model simulations and a state-of-the-art weather forecasting system. The post-holder will have the opportunity to teach
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are not designed to produce reliable regional estimates of those phenomena. Therefore, small area estimation (SAE) methods are used. With technological advances, Big Data now offers valuable spatial
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with the possibility of renewal. This project addresses the high computational and energy costs of Large Language Models (LLMs) by developing more efficient training and inference methods, particularly