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trade-offs between predictive performance, computational efficiency and scalability, using high-performance and cloud computing environments. Depending on the agreed research direction, you may also
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microbiome data (sequencing and gene chip data). Other responsibilities include: (i) managing different servers, pipelines, and cloud computing systems; (ii) coordinating the efforts for applying
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particular focus on data interoperability and on the integration of AI models, multi-agent systems, and intelligent workflows deployed across the Edge–Cloud–HPC Continuum. The research activities
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position. Associate Professor / Senior Lecturer in Computer Science Area: Emerging Technologies (Machine Learning, Cyber Security, AI, Cloud Computing) Primary Responsibilities Teach assigned undergraduate
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and the tools required to make data driven discoveries that increase our scientific knowledge and improve the quality of life. We architect ecosystems of large-scale commons of research data, computing
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, database theory, and edge and cloud computing, this research will pave the way for a new reasoning paradigm that unites the expressiveness of materialisation with the efficiency of virtualisation. You
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architecture, including networking, cloud, end user computing, hosting, data centres, storage, virtualisation and core infrastructure services. They will lead a small team of domain architects, establish
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across large-scale clinical environments. What You'll Do: Design, build, and optimize distributed data processing workflows utilizing technologies such as PySpark, Dask, and cloud-based computing
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, data analysis, and visualization environments/IDEs (e.g., R/R Studio, Python/Spyder/VSCode) Familiarity with GIS methods and cloud-based computing resources (e.g., Google Earth Engine) for large-scale
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with fundamental programming concepts, frameworks, languages and technologies such as SQL, C#, .NET, Java, XML, and JSON. Familiarity of Cloud Computing fundamentals; specifically, iPaaS, IaaS, SaaS