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be finalised by July 2026. Supported Areas for START Infocomm Technology Information Security: Mobile security, cyber-physical systems, IoT security, security analytics, operational cybersecurity
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statistical and computational methods designed to use “big data” and to address questions of direct or indirect relevance to common complex diseases and disorders. The appointee will join the group of Professor
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candidate must have experience in the following areas: molecular cell biology, plant phenotyping, and image/data analysis, as well as working as part of a large team. A track record of publishing research is
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Python) Experience in analyzing large and/or complex datasets Interest in quantifying uncertainties for computer models and/or climate predictions Ability to work in a team Ability to communicate orally in
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opportunity to join a dynamic and inclusive research team at University College Cork (UCC), working within the large-scale national Research Ireland (formerly Science Foundation Ireland) funded CONNECT Centre
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considered. The successful candidate must have experience in the following areas: molecular cell biology, plant phenotyping, and image/data analysis, as well as working as part of a large team. A track record
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evaluation of North Atlantic jet-stream changes in large numbers of state-of-the-science global climate model simulations that have recently been produced by key inter/national projects, using the latest
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to analyse datasets Experience in statistical or scientific programming (ideally R and/or Python) Experience in analyzing large and/or complex datasets Interest in quantifying uncertainties for computer models
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R or equivalent skills in another relevant language. We are not expecting you to be an expert in all forms of computer simulation, Large Language Models, or machine learning etc, but a working
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challenges of our time, with rising ideological divides and fragmented information ecosystems coinciding with increasing stress, anxiety, and declining well-being. Polarizing online content not only fuels