Offer Description
Doctoral Candidate 15 (DC 15) – Enhancing water distribution management through District Information Areas: A data-driven approach to optimization and automation
Newcastle University (UNEW), UK, 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 Newcastle University and will work under the supervision of Dr Manuel Herrera.
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 candidate will contribute with the following subobjectives:
1) Develop and implement a DIA framework that uses virtual subnetworks based on connectivity and shared data, enabling semi-autonomous local decision-making. This framework aims to enhance automation in WDSs by synchronizing and coordinating with existing DMAs to optimise network efficiency and resilience.
2) Incorporate sensors and smart meters within the DIAs to improve data collection and analysis. This integration seeks to enhance the ability to self-evaluate local network health and conditions, facilitating more efficient WDS management.
Expected Results:
1) Enhance DMA management by DIAs localised decisions informed by both local network evaluations and information from neighbouring areas, leading to improved operational efficiency and resilience.
2) Enhance the existing sensor network to achieve comprehensive coverage of the WDS, providing an accurate representation of the physical infrastructure and paving the way for the development of a large-scale digital twin.
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 supervisor, a co-supervisor 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), Brussels (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 facilitate 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: manuel.herrera@newcastle.ac.uk
Skills/Qualifications
• Water engineering
• Asset management
• Infrastructure resilience
• Trustworthy AI
• Network science
• Decision support systems
• Python, R, Julia or related programming languages
• Data integration and interoperability
• Scientific writing in Latex
• Teamwork
Specific Requirements
To be admitted, candidate must meet the requirements for access to a doctoral programme in Civil Engineering at Newcastle University.
Candidates must also comply with all applicable eligibility requirements and regulations of the Marie Skłodowska-Curie Actions (MSCA) Doctoral Networks programme.
Additional Information
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’ CV and motivation letter 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: The employment contract will have a duration of 36 month starting by 1srt january 2027.
Research field: Artificial Intelligence
Applicants whose first language is not English require an IELTS score, or equivalent, of 6.5 overall with a minimum of 5.5 in all sub-skills.
