Job Information
- Organisation/Company: University College Dublin
- Department: UCD School of Civil Engineering, University College Dublin
- Research Field: Engineering » Computer engineering; Mathematics » Statistics; Computer science
Offer Description
Doctoral Candidate 9 (DC 9) - A multi-source data fusion approach to modelling the impact of hydro-meteorological extremes on WDS water quality
The University College Dublin (UCD), Ireland, is recruiting a Doctoral Candidate (DC) within the Horizon Europe Marie Skłodowska-Curie Doctoral Network i3WaterS – Intelligent, Innovative and Integrative Water Systems.
The successful candidate will be enrolled in a PhD programme at UCD and will work under the supervision of Dr David Ayala-Cabrera, the co-supervision of Dr Soumyabrata Dev, the co-supervision of Dr Isabel Douterelo Soler, and the mentoring for Water industry expert.
i3WaterS brings together leading universities, research centers, technology developers and water utilities across Europe. The project will train 15 Doctoral Candidates to develop innovative AI-driven solutions for intelligent, resilient and sustainable water systems, contributing to the digital transformation of one of the most critical infrastructures for society.
The risk of water scarcity due to climate change and human activities is real. i3WaterS stands for Intelligent, Innovative, Integrative Water Systems and addresses the urgent need to optimize water resources management by providing a comprehensive solution to upgrade, optimally operate and maintain water distribution systems (WDSs). For the first time, a unique holistic approach will find the key interrelationships between external, day-to-day and extreme, factors and WDS failures, to advise actions and protocols to make WDSs robust and reliable.
At research level, i3WaterS project focuses on the integration of data, specific expert knowledge and computational simulations tools, introducing the most advanced data-driven and artificial intelligent techniques beyond the State of the Art, that plugged in a newly developed intelligent decision support system (IDSSs), working as an umbrella for a set of 14 independent solutions that enables assisting the WDSs management into scientifically driven decision-making. The incorporation of artificial intelligence (AI) will help to increase the autonomy of some parts of the WDS, those suitable under a paradigm of maximum security, safety and robustness, and the project will take care to frame this autonomy in a global and general concept of intelligent assistance, including human validation in each steps where it makes sense 15 Doctorate Candidates will learn from a network of experts on network monitoring, data management, algorithms, AI, modeling, microbiology, ethics and industrial partners, and by participating in a specifically designed training programme, they will develop the required cross competencies to find, test and innovate over a solution that will be fundamental to meet the sustainable development goals on water. Just as important, i3WaterS provide a new generation of internationally connected professionals with unique skills for the development of thriving careers in the critical infrastructures.
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:
- Collect/categorize the specific pathways through which climate change and extreme hydro-meteorological events degrade water quality in WDSs.
- 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:
- A robust methodology for identifying and classifying extreme events that pose high risks to WDS water quality
- An enhanced numerical model capable of simulating complex water quality responses to extreme meteorological triggers.
- 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.
Training Programme
The training proposed by i3WaterS will uniquely integrate decades of knowledge, expertise & achievements in disciplines such as civil and computer engineering, hydroinformatics, geomechanics, applied mathematics, multiobjective optimization, high performance computing, big data, artificial intelligence, modelling, and data management, including soft skills facilitated by academic and non-academic partners.
Apart from the PhD thesis done under a multidisciplinar and international supervisory panel composed by a supervisor, a co-supervisor(s) from a second i3WaterS university and an industrial mentor linked to a real water facility, the program includes an International Doctoral School with six training chapters that take place under an international mobility structure (Barcelona (Spain), Dublin (Ireland), Bordeaux (France), Delft (The Netherlands), Bussels (Belgium), NewCastle (UK)). The contents of the training programme include the most relevant and advanced topics related with smart resilient WDSs and soft skills for the researchers and professionals of the future. The following topics are included in these training chapters:
- Artificial Intelligence and Machine Learning.
- Explainable AI and Trustworthy AI.
- Knowledge Representation and Semantic Technologies.
- Multi-Agent Systems and Intelligent Decision Support Systems.
- Digital Twins and Smart Water Systems.
- Innovation, entrepreneurship and technology transfer.
- Scientific communication and transferable skills.
International mobility will easy connections and visits to water facilities all over Europe, and industrial secondments will give a realistic perspective.
Two International Secondments in other second real water facilities will allow extensive testing and validation of thesis findings to guarantee real contribution to the state of art. These Secondments into industrial partners are included with two aims: testing the PhD findings in a different water facility from the one supporting the project development, and to allow providing specialised training to the water utilities staff.
Main Supervisor: Dr David Ayala-Cabrera (UCD, Ireland)
Co-supervisor: Dr Soumyabrata Dev (TCD, Ireland) and Dr Isabel Douterelo Soler (USFD, UK)
Industrial Mentor - Water industry expert
Where to apply
E-mail: david.ayala-cabrera@ucd.ie
Requirements
Research Field: Engineering » Computer engineering
Education Level: Bachelor Degree or equivalent
Research Field: Mathematics » Statistics
Education Level: Bachelor Degree or equivalent
Research Field: Computer science
Education Level: Bachelor Degree or equivalent
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
Specific Requirements
Candidates must also comply with all applicable eligibility requirements and regulations of the Marie Skłodowska-Curie Actions (MSCA) Doctoral Networks programme.
Mobility Rule:
- Applications are accepted from candidates from Ireland, the EU and worldwide.
- Applicants must comply with the Marie Sklodowska-Curie Actions (MSCA) mobility rule. At the date of recruitment, candidates must not have resided or carried out their main activity (work, studies, etc.) in Ireland for more than 12 months during the 36 months immediately preceding the recruitment date. Short stays such as holidays are not taken into account.
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.
Employment conditions are subject to the legislation and internal regulations of the recruiting institution.
Languages: ENGLISH Level: Excellent
Additional Information
Benefits
Contribution for Recruited Research Over 36 months (*The amounts offered are subject to legal contributions, e.g. all employer-related costs, income tax)
- Living Allowance: 196907.04€ * (per 36 months)
- Mobility Allowance: 25560.00€* (per 36 months)
- Family allowance: 17820.00€* (per 36 months)(where relevant)
- Successful candidate will have the opportunity to be part of the UCD Structured PhD programme. This programme offers several innovative and high-quality measures designed to support UCD PhD students to achieve academic and professional objectives. Further details about the UCD Structured PhD programme can be found at https://www.ucd.ie/graduatestudies/researchprogrammes/structuredphd/
- Secondment 1. 3-months secondment at USFD (supervised by Dr Douterelo). The DC will receive a specialized training on optimally placed smartified, resilient water quality, impacts on water quality at USDF and will conduct/receive a data collection/mentoring at VIT. Interaction with DC3.
- Secondment 2. 2-months secondment at CET (mentor Dr Arnaldos) for testing and validating the findings.
Eligibility criteria
All candidates who cannot provide proof of the required academic qualification will be immediately excluded from the selection process.
The selection process will have 2 steps:
1st step: Curriculum Vitae
All CV lines should be accompained with documentarion to prove and evidence the content of the line.Those non proved will not be considered
Curriculum vitae will be evaluated according to the following general criteria:
The maximum score for candidates who meet all the requirements set out in the job offer will be 10 points.
Each category will be scored between 0 and 10.
- Required specialization.
- Required academic training.
- Technical competencies.
- Organizational competencies.
- Professional experience.
- Any aspect of the candidate’s professional profile that the selection committee considers particularly relevant.
CV Final Score = 0.1*required specialization + 0,2* Required Academic Trainer+0,2*Technical Competences + 0,1*Organizational Competences + 0,3* Professional Experience + 0,1*Candidates professional Profile
The minimum qualification to pass the CV step is 5.
2nd Step:
only candidates who have obtained a score of 5 or higher in their CV will be shortlisted for the interview.
The interview will be evaluated according to the following criteria:
Each category will be scored between 0 and 5
- Suitability to the functional competencies of the position.
- Relevance of professional experience.
- Any aspect of the candidate’s professional profile that the selection committee considers particularly relevant.
Interview Maximum Score= 0.4*suitability to the functional competencies + 0.4*relevance of professional experience+0.2*aspect of the candidate’s professional profile
The minimum qualification to pass the interview step is 3
Eligible candidates will be ranked from highest to lowest score, which will be the selection criterion.
Selection process
Once the application submission period has ended, the secretary of the selection committee may contact applicants to request any mandatory documentation that has not been provided, or to ask for additional documentation needed to evaluate the application.
The Evaluation Committee will carry out an initial assessment of the eligible candidates’ CVs and, if deemed appropriate, will invite those who pass this stage to take part in tests and/or interviews. The date and location of the interviews and/or tests will be set by the committee and will be communicated in advance to the selected candidates via the email address provided in their application.
Candidates must be available to carry out the test and/or interview using an online platform.
Additional comments
Contract duration: 36 months. In the event that the successful candidate is recruited after 1 January 2027, the contract duration will be adjusted accordingly and will end no later than 31 December 2029.
Research field:
- Engineering
- Mathematics
- Statistics
- Computer Science
- Artificial Intelligence
- STEAM Related Area
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).
Documentation:
- Motivation letter is required, clearly explaining why the applicant is a strong candidate for this specific position and how their background and interests match the research topic.
- Detailed CV
- Academic transcripts,
- Any other supporting documents requested by the recruiting institution.
Website for additional job details: https://websk.upc.edu/i3waters
Work Location(s)
Number of offers available: 1
Company/Institute: UCD School of Civil Engineering, University College Dublin
Country: Ireland
City: Dublin
Street: University College Dublin, Richview Newstead Belfield Dublin 4, Dublin
Contact
City: Dublin
Website: https://www.ucd.ie, https://www.ucd.ie/civileng
Street: University College Dublin, Richview Newstead Belfield Dublin 4
E-Mail: david.ayala-cabrera@ucd.ie
Phone: +353 1 716 3280
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