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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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large-scale whole genome and whole exome sequencing, RNA-seq, ATAC-seq, proteomics, and metabolomics data in a well-established cohort of childhood cancer survivors with clinically ascertained deep
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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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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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position. Applicants should have a PhD degree (or expect to receive a PhD degree by June 15, 2025) in Psychology or allied fields (e.g., Sociology) with an interest in conducting research relevant to racial
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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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and archival data, as well as working towards future observing proposals and strategies. Within this framework, the successful candidate will have flexibility and freedom to tailor the project
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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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science or related fields and demonstrated record of productivity and publications. Experience with analyzing large-scale genomic data. Application Requirements Document requirements Curriculum Vitae - Your most
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physical models. However, to achieve reliable results choosing the right methodology and training strategy is a large scientific challenge. Your job In this project, we aim to apply deep learning techniques