| Code | i3WaterSDC10 |
|---|---|
| Host Institution | Universitat Politècnica de Catalunya Intelligent Data Science and Artificial Intelligence Research Center (Universitat Politècnica de Catalunya) |
| Location | Barcelona, 08034 |
| Supervisor(s) | Main Supervisor: Prof Karina Gibert (UPC, Spain) Co-supervisor: Dr Manuel Herrera (UNEW, UK) Industrial Mentor – Experts: Dr Marina Arnaldos (CET, Spain) |
| Research Field | Artificial Intelligence |
| Contract type | Fixed term contract — Full time, 37.5 h/week |
| Application Deadline | September 15th, 2026 |
Description
Research Objectives
The main research goal of iWaterS 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 the Integration of different data-driven models and reasoning capacities in a single system providing holistic support to WDSs. Introduction of reasoning capacities that provide explainability to different recommendations global treatment of both numerical and qualitative variables. Mix approach where data-driven and knowledge-driven components are combined
The doctoral research will focus on the development of an Intelligent Assistant for the supervision and management of water distribution systems, integrating symbolic and data-driven Artificial Intelligence techniques into a hybrid decision-support framework.
The project offers 15 DC and this candidate will define a general purpose IDSS architecture for the holistic management of WDSs. The rest of candidates will integrate into the global system by plugging their solutions into the IDSS of this candidature.
Therefore, the candidate will contribute to generate a hybrid AI plug and play architecture for holistic management of smart WDS with the following subobjectives:
1. Designing the overall architecture of a next-generation Intelligent Decision Support System (IDSS) for smart water distribution networks.
2. Developing a plug-and-play data acquisition and integration layer capable of handling heterogeneous information sources, including IoT sensors, SCADA systems, hydraulic models, Ground Penetrating Radar (GPR) data and other operational datasets and offline data.
3. Development of the partial knowledge components required for the semantics management of the tool, and expert specific knowledge on WDS facilities
4. Development of reasoning engine and argumentative capacities for the explainability model (XAI).
5. Development of the automatic reporting and visualization modules and integration with pieces from other DCs.
6. Contextualization in the real case of reference water industry.
7. Prove of concept with selected predictive models and metamodels developed by other doctoral candidates within the i3WaterS network.
8. Validating the proposed framework through real-world case studies in a second water industry.
9. Generalization the proposed architecture in a third water industry.
Requirements
Education level
Master Degree
Skills / Qualifications
- Machine Learning and Data Mining
- Knowledge-Based Systems
- Data-driven models
- Explainable Artificial Intelligence (XAI)
- Multi-Agent Systems
- Decision Support Systems
- Python, R, Java or related programming languages
- Data integration and interoperability
- Documenting in Latex
- Teamwork
Required languages
English – C1
Spanish or catalan will be taken into consideration
