Offer Description
Doctoral Candidate 3 (DC3) – ISmartification of water quality and safety monitoring for water distribution systems
The University of Sheffield (USFD, 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 USFD and will work under the supervision of Dr Isabel Douterelo Soler, the co-supervision of Dr Manuel Herrera and Dr David Ayala, and the mentoring of a 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 specific research objective of this offer is To develop intelligent monitoring and predictive models that integrate microbial, environmental and hydraulic information for the early detection of water quality risks and improved resilience of drinking water distribution systems.
Therefore, the candidate will contribute with the the following subobjectives:
1) Obtain a robust data set (microbial, environmental and hydraulic parameters) combining data from experimental tests and field work in real networks and service reservoirs, essential to modelling of resilience and vulnerability to microbial contamination.
2) To develop cutting edge methodologies such as graph convolutional neural networks to detect and predict contamination events in response to infrastructure failures and extreme weather events.
3) To provide insights into the dynamics of biofilms, and interdependencies between microorganisms and infrastructure over time, under different scenarios.
Expected Results:
1) Development of geometric deep learning, time-series data mining, and agent-based approaches incorporating microbial information for WDSs.
2) Criticality performance indicators for WDSs.
3) Tools for infrastructure vulnerability analysis and predictive maintenance models.
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), 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 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 Isabel Douterelo Soler (USFD, UK)
Co-supervisor: Dr Manuel Herrera (UNEW,UK) & Dr David Ayala-Cabrera (UCD, Ireland)
Industrial Mentor – Water Industry Expert
Where to apply
E-mail: i.douterelo@sheffield.ac.uk
Skills/Qualifications
. Experience (or interest) in urban water sector, including research, industry or public sector.
. Aptitude for research in drinking water systems, including machine-learning and ecological modelling.
. Experince with Python, R or related programming languages for analysis of large datasets.
. Experience (desirable) with molecular work including DNA sequencing and bioinformatics
. Willingness to collaborate with other researchers, industry and end-users.
. The candidate is expected to publish her/his research in scientific journals and conferences.
. Strong organisational skills.
Specific Requirements
An upper 2.1 or first class honours degree or equivalent in Civil and/or Environmental Engineering / Environmental Sciences/Physical Geography or similar 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 / Environmental Sciences or a related area may also be suitable.
Candidates must comply with all applicable eligibility requirements and regulations of the Marie Skłodowska-Curie Actions (MSCA) Doctoral Networks programme.
Doctoral Status: Applicants must not possess a doctoral degree at the date of recruitment.
Mobility Rule: 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 Italy for more than 12 months during the 36 months immediately preceding the recruitment date. Short stays such as holidays are not taken into account.
Employment conditions are subject to the legislation and internal regulations of the recruiting institution.
To be admitted, candidate must meet the requirements for access to a doctoral programme in the School of MAC at The University of Sheffield. https://sheffield.ac.uk/postgraduate/phd/apply
Additional Information
Benefits
£42,702 (gross annual per annum) + £5,926 (gross mobility allowance) + possibility of family allowance, if elegible.
Two secondments
Secondment 1. 3-months secondment at UCD (Ireland) (supervised by Dr. Ayala-Cabrera). This secondment will allow the DC to get training at UCD in hydrodynamics, water quality issues, extreme disruptive events, ND methods for monitoring/assessment and will conduct/receive a data collection/mentoring at BW.
Secondment 2. 2-months secondment at AQ (Spain) (mentor Mr Francés-Chust) for testing and validating the findings.
Eligibility criteria
Applicants must not hold a doctoral degree at the date of recruitment. Applicants may be of any nationality and must comply with the MSCA mobility rule: they must not have resided or carried out their main activity, including work or studies, in the United Kingdom for more than 12 months during the 36 months immediately preceding the recruitment date. 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.
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Candidates must be available to carry out the test and/or interview using an online platform.
Additional comments
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 (https://sheffield.ac.uk/postgraduate/english-language). Knowledge of or willingness (desired) to learn other languages in particular those associated with your secondments (i.e. Spanish).
Contract duration: The employment contract will have a duration of 36 month starting by 1srt january 2027.
Research field: Artificial Intelligence, Civil and Environmental Engineering (water), Environmental Science
Website for additional job details: https://websk.upc.edu/i3waters
