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24 Months Specific purpose whole-time post This role is part of a national operations team for Rinn Artificial Intelligence – Research & Innovation in Data Science and AI, a multi-institutional
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28 Jul 2026 Job Information Organisation/Company University of Galway Research Field Computer science » Other Researcher Profile Recognised Researcher (R2) Positions PhD Positions Application
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-cognition, exposome and neuroimaging data. Under the supervision of Professor Agustín Ibáñez, the Fellow will contribute to harmonisation international datasets and developing multimodal statistical and
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10 Jul 2026 Job Information Organisation/Company University College Cork Department HR Research Research Field Information science » Other Researcher Profile Recognised Researcher (R2) Positions
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/3rdAI For an information package including full details of the post, selection criteria and application process see https://ore.ucc.ie/ The University, at its discretion, may undertake to make
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Post Doctoral Researcher Rinn Artificial Intelligence – Research & Innovation in Data Science and AI
24 months, Fixed Term, whole-time Post Applications are invited for a Post-Doctoral research position within the Rinn Artificial Intelligence – Research & Innovation in Data Science and AI funded by
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Intelligence – Research & Innovation in Data Science and AI funded by Research Ireland, led by Professor Barry O’Sullivan in the School of Computer Science & Information Technology. This role is part of a
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Applications are invited for the following position: Title of Post: UL Programme Manager for Rinn AI National Centre in Data Science & AI JOB SYNOPSIS This role is part of a national operations team
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researchers in materials science and industry. More information can be found at http://ambercentre.ie About the Trinity Centre for Biomedical Engineering (TCBE): TCBE is a key research centre in Trinity College
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Digital manufacturing, Industry 4.0, or cyber-physical systems o Product design for disassembly, remanufacturing, or recycling o Data analysis, AI, or machine learning applied to engineering systems