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: CBRAIN is a flexible Ruby on Rails framework for accessing and processing large amounts of data across a distributed network of High Performance Computing (HPC) and Cloud Computing infrastructures. In
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: Department of Atmospheric and Oceanic Sciences Position summary: Conduct organized research focused on active and passive remote sensing of clouds and precipitation systems with minimal supervision. Contribute
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management. Oversee modernization of McGill’s enterprise platforms, including Banner 9, and implement composable, cloud-based solutions to ensure flexibility and scalability. Champion a seamless, user-centered
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Sciences. The project will examine aerosol–cloud interactions related to climate change, with a focus on aerosol optical properties and their three‑ and four‑dimensional physico‑chemical characteristics
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training programs. Deliver annual or semi-annual awareness campaigns (e.g., phishing simulations, research data protection, cloud usage). Manage the Information Security team, including hiring, performance
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, payment completed (ie Software/ other Vendors) Use Case Library Design & Development Collate, anonymize and organize all client PoC work (with support from Cloud Engineer) Other Qualifying Skills and/or
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). The Bioinformatics Analyst position corresponds to junior members of the team with expertise in large-scale genomic analyses, software development using R and Python, and High-Performance and Cloud computing
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environment. Other Required Skills and Abilities Demonstrated ability to manage and analyze large, multi-modal datasets. Familiarity with cloud computing environments (e.g., Google Cloud) and version control
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SecureData4Health (SD4H) OpenStack cloud infrastructure. It currently includes 15,000 VCPU, 60 Petabyte of storage, 30 GPU and is growing as additional academic research projects join. The Software Infrastructure
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other visual media including photos, maps, and graphs. Execute informed tradeoffs in accuracy, performance, and cost across model families, model sizes, and inference settings (local vs. cloud). Review