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of Computer Science and Information Technology, to work on Insight Platform research in the area of multi-agent pathfinding in dynamic environments. In addition, the researcher may contribute to various other
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, Mathematical Modelling and Self-Learning Systems, and Data Science and Analytics as well as a strong PhD programme. The Mathematics Group comprises nine permanent members of staff working across the areas
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cancers and inflammatory conditions. The research project is supported by a Research Ireland-funded Frontiers for the Future Award programme. We are seeking highly motivated candidates with a PhD and
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for Data Analytics, based at the School of Computer Science & IT, University College Cork, Ireland. The Post-Doctoral Researcher will work in the intersection of various ongoing projects related to user
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developed by the Offshore Renewable Energy group to model project scenarios. • Collaborating with team members to adapt simulation tools based on project needs. • While primarily contributing to the IDEA-IRL
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-clinical models. They will coordinate and participate in network collaborations to investigate tissue-resident immunity and protection against challenge. They will work closely with an experienced graduate
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for Data Analytics, based at the School of Computer Science & IT, University College Cork, Ireland. The postdoctoral researcher will work on the AI4Europe EU project. This position is highly
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interdisciplinary study that will assess the pre-/and post-radon concentrations following deep energy-retrofits scenarios of the large-scale national renovation strategy. INFORM will utilise a building physics model
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concentrations following deep energy-retrofits scenarios of the large-scale national renovation strategy. INFORM will utilise a building physics model (CONTAM), which will be parameterised based on representative
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, Materials & Structures, Observations & Operations, Coastal & Marine Systems, Bioenergy, Energy Policy & Modelling and Renewable Energy Management. Lir NOTF houses Ireland’s only infrastructure for small