University College Dublin
2 weeks ago
Scholarship/Assistantship
PhD in multi-source data fusion for modelling hydro-meteorological extremes and WDS water quality University College Dublin in Ireland
Degree Level
PhD
Field of study
Computer Science
Funding
Scholarship/assistantship position; fixed-term full-time doctoral contract (40 h/week). The post is presented as a funded PhD opportunity, but no stipend amount or tuition details are stated in the text.
Deadline
Sep 30, 2026
Country
Ireland
University
University College Dublin

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About this position
PhD opportunity at University College Dublin (UCD School of Civil Engineering, Dublin, Ireland) on multi-source data fusion for modelling the impact of hydro-meteorological extremes on water distribution system (WDS) water quality.
The project sits at the intersection of Civil Engineering, Environmental Science, Computer Science, Mathematics, and Statistics. The research aims to combine numerical modelling, Earth Observation (EO), geolocation data, and in situ water-quality measurements to build explainable, AI-driven predictive frameworks for resilient water management under climate-change stressors such as floods and droughts.
Key research tasks include identifying pathways by which extreme events degrade WDS water quality, quantifying impacts using geospatial and EO data, and developing/validating intelligent data analysis algorithms for forecasting water-quality fluctuations under future socio-economic and climatic scenarios. Expected outputs include a methodology for classifying high-risk events, an enhanced numerical model for complex water-quality responses, and AI models for real-time and offline prediction.
Eligibility highlights: applicants must not already hold a doctorate; a first-class or upper second-class honours degree (or equivalent) in Engineering, Mathematics, Statistics, Computer Science, or a related discipline is required, and a relevant STEM Master's degree may also be suitable. Desired skills include water-sector experience, modelling, optimization, Python/MATLAB/R/Java, machine learning, data mining, explainable AI, multi-agent systems, decision support systems, data integration, and LaTeX. Strong English communication, teamwork, and organizational skills are expected.
Funding/status: the post is advertised as a Scholarship/Assistantship and a fixed-term full-time doctoral contract (40 h/week). No stipend amount is stated in the post.
Deadline: 30 September 2026. Apply by email to [email protected] and/or via the linked recruitment portal. An EURAXESS listing is also provided for reference.
Funding details
Scholarship/assistantship position; fixed-term full-time doctoral contract (40 h/week). The post is presented as a funded PhD opportunity, but no stipend amount or tuition details are stated in the text.
What's required
Applicants must not already hold a doctoral degree at the date of recruitment. A first-class or upper second-class honours degree, or equivalent, in Engineering, Mathematics, Statistics, Computer Science, or a cognate discipline is required; an upper second-class Master's degree in a relevant STEM area may also be suitable. Desired experience or interest includes the urban water sector, water quality or hydraulic modelling, optimization, data analysis tools such as Python, MATLAB, R or Java, intelligent data analysis, machine learning, data mining, explainable AI, multi-agent systems, decision support systems, data integration/interoperability, and LaTeX. Strong teamwork, independent working, organizational skills, publication potential, and excellent English communication are required; willingness to learn other languages such as Spanish is desirable.
How to apply
Apply by email to [email protected] using the subject line and application details in the mailto link, or use the recruitment portal linked in the post. Review the EURAXESS listing if needed for additional context. Submit before 30 September 2026.
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