Offer Description
Hybrid AI for Sustainable Management of Water Distribution Systems (WP3) + i3WaterS
i3WaterS brings together leading universities, research centres, 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 objective of the project is the protection of drinking water distribution systems (WDSs) and their consumers from the adverse impacts of climate change and human activities. For the first time, a unique holistic approach will identify the key interrelationships between external, day-to-day, and extreme factors and WDS failures, advising actions and protocols to make WDSs robust and reliable.
The purpose of this PhD research is to develop tools and methods for sustainable management of water distribution networks. Specifically, operational management will aim to regulate pressure and velocity within the distribution system. This will help to achieve two primary objectives: ensuring water quality and minimizing leakage.
The specific research objective of this offer is To develop advanced hydraulic and numerical modelling techniques that improve the simulation, calibration and operational management of drinking water distribution systems under complex and dynamic conditions.
The candidate will contribute with the following subobjectives:
Objectives: 1) Increase the detection threshold and location of leakage flows for real case studies, using only pressure data;. 2) Sustainable operation of a WDS network (with pressure and flow regulation) to reduce background leakage, sedimentation, and pipe fatigue. 3) Adapt a WDN to extreme events and mitigate degraded service levels.
Exp. Results: 1) New hybrid AI algorithms for a better detection and localization of leakage. 2) Gain measurements for additional sensors and actuators. 3) New hydraulic model handling flow velocity and pressure constraints.
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 an advisor, a coadvisor 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.
Where to apply
E-mail: job-ref-os797a84sq@emploi.beetween.com
Skills/Qualifications
Modelling and optimization skills
Knowledge of machine learnings
background in mathematics
Experience with Python or other programming languages
Excellent analytical and problem-solving skills
Ability to work independently and in a team
Scientific writing skills and motivation to promote result• Machine Learning and Data Mining
Specific Requirements
To be admitted, candidates must meet the requirements for access to the doctorate set out in article 6 of Royal Decree 99/2011, of January 28.
You’ll have to comply with the Working Laws in France as well.
Additional Information
Benefits
36-month fixed-term contract to be filled in October 2026
The gross salary amounts to approximately €3,860 per month (subject to employee contributions and income tax).
The position is funded under the Marie Skłodowska-Curie actions and offers remuneration in line with the European Commission guidelines. This includes a monthly subsistence allowance and a mobility allowance of €710. A family allowance of €660 per month is paid where applicable. The above-mentioned subsistence and mobility allowances correspond to employers’ contributions and are subject to social security contributions in France.
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.
NB. Please note that the position is based in a laboratory located in a restricted area, which requires a pre-employment background check that can take up to eight weeks to complete.
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
Please note that the position is based in a laboratory located in a restricted area, which requires a pre-employment background check that can take up to eight weeks to complete.
