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Learning (ML), Generative AI and modern cloud architectures. This role blends deep technical expertise with strategic leadership — influencing stakeholders, shaping policy and embedding sustainable AI
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cloud computing, IoT, and AI. Strong communication and leadership skills, with the ability to present complex concepts to diverse audiences. Apply now
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the experimental design phase to ensure resulting data sets properly address research inquires. Oversight of computing clusters, either on campus, at remote sites, or in the cloud. Duties: Analyzes large data sets
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is delivered through a blend of traditional on-premises and hybrid-cloud deployment models and underpins business-critical services across the University. The Senior Technical Lead will report on
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the Assistant Director on system modernization efforts, including migration of on-premises systems to cloud-based services. Maintain working knowledge of, and contribute to, systems and frameworks such as
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, experimentation, development and testing JFN: MLS operational architecture including nodes, hub, network, software baseline and CI/CD apparatus (e.g. IL-5 up to IL-7 Cloud Develop and maintain automated reporting
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Expertise: Deep understanding of enterprise platforms (ERP, HRIS, Finance, Procurement). Experience with integration architecture, data management, and analytics. Familiarity with cloud-based SaaS ecosystems
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important IT and digital transformation projects. These may include core systems implementations, cloud and infrastructure upgrades, cyber security initiatives, enterprise applications, data platforms, and
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critical clinical applications. This role bridges clinical operations and information technology, ensuring that complex cloud‑based and on‑premise systems operate seamlessly as an integrated ecosystem
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knowledge of server and system security, backup and recovery, and hardware maintenance will be an added advantage. Experience with shared storage and enterprise networking technologies. Exposure to cloud