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these data models. Formulate process for automated insights to management using advanced BI tools. Develop and maintain an in-house market intelligence hub and produce regular and ad-hoc reports to inform
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. The role will involve continued system review to improve efficiency, reduce data handling through automation, and improve and develop data analytics reporting and dashboards to support ongoing business
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Automated Program Repair (APR) is the grand challenge in software engineering research. Many APR methods have shown promising results in fixing bugs with minimal, or even no human intervention
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, cabling, UPS systems, and environmental controls, including lifecycle activities like refreshes, replacements, and maintenance. Coordinate infrastructure optimisation initiatives, including footprint
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user training for Generative AI solutions across all domains of the organisation. Develop Proof of Concept Gen-AI solutions in Azure or AWS. Setup, run and monitor automated test plans and scenarios
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of senior researchers, engineers, postdocs, and PhD students working together toward impactful science and mutual growth. In this role, you will apply your expertise in aquatic biogeochemical and ecological
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integration patterns, data validation frameworks, and data quality management Experience working with Artificial Intelligence/Machine Learning data requirements and establishing data pipelines for automated
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technical controls across the University’s cloud and infrastructure ecosystems. Working closely with delivery teams, enterprise architects, and the CISO, you will help ensure that security is embedded
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: Deep understanding and implementation of Kubernetes networking, utilising CNI plugins, ingress controllers, and service meshes to ensure efficient and secure communication within the cluster. Applying
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the University to: Provide a unified, 360-degree view of each student that will enhance our ability to engage with them (including privacy protections and controls) Support the transformation of business processes