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/c-caps/), led by Prof. Jurgita Ovadnevaite, and to facilitate Climate modelling activities under the Epic-Air project (universityofgalway.ie/epic-air/) . Salary: Postdoctoral Researcher salary scale
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for Climate and Air Pollution Studies (universityofgalway.ie/c-caps/), led by Prof. Jurgita Ovadnevaite, and to facilitate Climate modelling activities under the Epic-Air project (universityofgalway.ie/epic
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that provides data-driven prediction model and an automated dynamic decision model. This is a research focused role, where you will conduct a specified programme of research supported by research
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of scaling models, business model development, and funding strategies in education. Knowledge and understanding of policy, practices, and procedures that are relevant to the role, to include knowledge and
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modelling, and real-time graphics programming. Proficiency in programming languages such as C++, C#, Python, or JavaScript. Strong understanding of UX/UI principles for immersive experiences. Experience in
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population estimation and modelling of population movements in the context of examining population exposure to extreme sea levels in low-elevation coastal zones (LECZ) in Ireland. In so doing, insight will be
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of the research group is to model genetic diseases using gene editing tools such as CRISPR/Cas9 to gain a better understanding of the mechanisms at play and to find alternative treatments. Based on previous work in
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benchmarking of national and international cancer research strategies, governance models and funding mechanisms. Qualitative Research: Lead and support qualitative and quantitative data collection, including
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the project entitled Modelling and measuring agricultural management on peat soils to enhance removals and sequestration of carbon (MAPSERS-C) that is funded by the Department of Agriculture Food and the Marine
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. Niamh Cahill. The core concept of this project will be to bring together and deploy cutting-edge approaches to small-area population estimation and modelling of population movements in the context