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, cloud computing, and distributed architectures, to enable efficient analysis of large-scale biomedical datasets. Collaborate with clinical and academic partners, both internally and externally, to ensure
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pipelines, proficiency in genomic association analyses, particularly involving large-scale datasets, and familiarity with cloud computing and/or high-performance computing (HPC) environments
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from state-of-the-art analytical tools and high-performance computing resources through the AWS cloud system and the UBC High Performance Computing Cluster, enabling efficient analysis at all stages
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with whole-genome or exome sequencing pipelines, proficiency in genomic association analyses, particularly involving large-scale datasets, and familiarity with cloud computing and/or high-performance
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: Prior experience with analysis of observational remote sensing data sets and/or numerical model output related to cloud properties is desirable. Strong computational skills, and ideally experience with
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. - Demonstrated ability to work with high-performance computing environments during academic training, with basic knowledge of cluster usage or cloud-based AI tools More Information Location: Kent Ridge Campus
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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. Qualifications/Requirements Qualifications / Discipline: - PhD from a reputable institution in Physics, Bio-imaging, Computer Science, or a scientific domain closely related to Machine Learning. - The candidate
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, toxicology, or pharmacology Understanding of biological pathways and their relationship to disease mechanisms or drug response Experience with cloud computing environments and large-scale data processing
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/or numerical model output related to cloud properties is desirable. Strong computational skills, and ideally experience with commonly used programming languages in the field (Python, MATLAB, IDL