35 evolution "https:" "https:" "https:" "https:" "https:" "UCL" research jobs at MAYNOOTH UNIVERSITY
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automatically by the system. Late applications will not be accepted. Maynooth University is an equal opportunities employer The position is subject to the Statutes of the University Where to apply Website https
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or responders out in the field. A suitably qualified candidate with an excellent primary degree and ideally postgraduate degree with significant backend web platform research and development expertise is required
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) on Tuesday the 6th of January 2026. Please note all applications must be made via our Online Recruitment Portal at the following link: https://www.maynoothuniversity.ie/human-resources/vacancies
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Tuesday the 6th of January 2026. Please note all applications must be made via our Online Recruitment Portal at the following link: https://www.maynoothuniversity.ie/human-resources/vacancies Applications
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applications must be made via our Online Recruitment Portal at the following link: https://www.maynoothuniversity.ie/human-resources/vacancies Applications must be submitted by the closing date and time
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. The successful candidate will play a key role in the design, development, and implementation of quantitative models and analytical frameworks to assess demand-side flexibility, distributed energy resources, and
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development of data architectures, analytics tools, and interoperability frameworks aimed at integrating building energy data into flexibility markets. They will work closely with an established team
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Sustainable Development Goals”. This person will continue and expand the successful outreach already achieved with focus on Transition Year, Initial Teacher Education and Industry Geomentors, introducing them
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researchers and a multidisciplinary team across institutions, contributing to the development, testing, and application of tools, datasets, and analytical methods used within the project. This role is intended
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the Department of Chemistry. The position is funded under a Research Ireland Pathways programme and will focus on the development of predictive computational models for advanced functional materials