i3WaterS › Doctoral positions

A multi-source data fusion approach to modelling the impact of hydro-meteorological extremes on WDS water quality

Description

Research Objectives

The main research goal of i3WaterS is to provide, for the first time, rational analyses and explainable intelligent decision support of WDS to increase resilience to day-to-day incidents and to extreme events in the context of climate change such as floods or droughts, through new interdisciplinary and integral approaches for exploiting datasets (on-line, off-line), intelligent models (data-driven, numerical) and simulation results (digital twins, multiagent systems).

The main research objective of this offer is To bridge that gap by integrating numerical modelling with Earth Observation (EO), geolocation data and Water quality in situ measurements. By leveraging Intelligent Data Analysis (IDA) for both online and offline datasets, this research moves beyond static assessments to create dynamic, AI-driven predictive frameworks that support proactive decision-making for future WDSs.

The candidate has the following specific objectives:

Objectives: 1) Collect/categorize the specific pathways through which climate change and extreme hydro-meteorological events degrade water quality in WDSs. 2) Quantify the impacts of extreme weather on WDS water quality by integrating numerical models with geospatial, EO, and water quality in situ measurements data 3) Develop and validate IDA-based algorithms to forecast water quality fluctuations under various future socio-economic and climatic stress scenarios.

Expected Results:

1) A robust methodology for identifying and classifying extreme events that pose high risks to WDS water quality 2) An enhanced numerical model capable of simulating complex water quality responses to extreme meteorological triggers. 3) A suite of data-driven, AI models designed for real-time and offline prediction of water quality trends, serving as a cornerstone for resilient water management strategies.

Requirements

Education level

Doctoral Status: Applicants must not possess a doctoral degree at the date of recruitment.

An upper 2.1 or first class honours degree or equivalent in Engineering / Mathematics / Statistics / Computer Science or cognate disciplines from an accredited institution. (Desired) An upper second class degree in a Master’s degree programme in an appropriate STEM area such as Engineering / Mathematics / Statistics / Computer Science or a related area may also be suitable.

Skills / Qualifications

• Experience (or interest) in urban water sector, including research, industry or public sector.
• Modelling (e.g. water quality and hydraulic modelling) and optimization (e.g. genetic algorithms) skills
• Experience (desirable) in the use of tool for analysing data; e.g. Phyton, MatLab, R or Java or related programming languages
• Experience (desirable) in intelligent data analysis; e.g. Machine Learning and Data Mining, Knowledge-Based Systems, Data-driven models, Explainable Artificial Intelligence (XAI), Multi-Agent Systems, Decision Support Systems, Python, R, Data integration and/or interoperability.
• Documenting in Latex
• Ability to work as part of a team, including collaboration with other disciplines but also independently.
• The candidate is expected to publish her/his research in scientific journals and conferences.
• Strong organizational skills.

UCD is committed to equality, diversity and inclusion. Learn more: www.ucd.ie/equality

Required languages

• Excellent communication skills in English, particularly in relation to report writing and delivering presentations. Further details on the UCD’s minimum English language requirements can be found at http://www.ucd.ie/registry/admissions/elr.html
• (Desired) Knowledge of or willingness to learn other languages ​​in particular those associated with your secondments (i.e. Spanish).