物联网与大数据水网系统分布式与集中式数据挖掘方向博士职位

Doctoral Candidate 11 (DC11) – Distributed and centralized data mining for WDS in the context of IoT and Big data (WP1) The Universitat Politècnica de Catalunya (UPC), Barcelona, Spain, 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 UPC and will work under the supervision of Ramón Pérez Magrané. 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. We are seeking a highly motivated and talented Doctoral Candidate (DC) to join our team for a PhD project titled: Distributed and centralized data mining for WDS in the context of IoT and Big data. Modern Water Distribution Systems (WDS) are rapidly evolving into smart, data-rich environments. This research project addresses the critical challenge of processing, validating, and extracting value from heterogeneous, high-frequency data streams. The project is structured around two core technological pillars: developing decentralized Artificial Intelligence (AI) models at the edge/sensor level, and implementing centralized advanced analytics in the cloud. The ultimate goal is to fuse both approaches, creating a synergistic framework where distributed and centralized intelligence enhance each other to optimize water network management. Key Responsibilities and Research Tasks: The research will be divided into three main operational phases: • AI-based Distributed Data Validation & Reconstruction: Develop a novel methodology leveraging AI/Machine Learning models for decentralized, automated data validation and data reconstruction directly at the source (edge/sensor level) to handle missing data or sensor anomalies. • Heterogeneous IoT Data Analytics: Explore, design, and implement advanced analysis systems (including AI frameworks, hydraulic and quality models) tailored for SensorThings (IoT) data. You will integrate and analyze diverse data streams originating from telecontrol (SCADA), laboratory analytics, maintenance logs, and external sources. • Framework Integration & Synergy Analysis: Integrate both distributed and centralized approaches into a unified platform. You will conduct comparative analyses to evaluate performance trade-offs and investigate how distributed and centralized results can mutually enhance system-wide accuracy and resilience.

Expected Outcomes & Deliverables: By the end of the PhD, the researcher is expected to have successfully developed and delivered: • Outcome 1: A robust methodology and software framework for Distributed WDS data collection and validation at the edge. • Outcome 2: An innovative Integration tool capable of seamlessly connecting live IoT data streams with hydraulic simulation models (e.g., EPANET). • Outcome 3: A fully functional Hybrid architecture that features decentralized data storage (at the edge/sensor level) coupled with centralized model management (in the cloud).

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 Ramon Pérez Magrané (UPC, Spain) Co-supervisor: Dr Mario Castro-Gama (VIT, The Netherlands) Industrial Mentor - Experts: Mr Sergi Grau Torrent (AM, Spain)

Requirements / required education level / degree: Master Degree or equivalent

Requirements / required education level / discipline: Computer science

Requirements / required education level / degree: Master Degree or equivalent

Requirements / required education level / discipline: Engineering

Requirements / required education level / degree: Master Degree or equivalent

Requirements / required education level / discipline: Engineering

Requirements / required education level / degree: Master Degree or equivalent

Requirements / required education level / discipline: Mathematics

Requirements / skills: Education: An outstanding Master’s degree (or equivalent) in Industrial Engineering, Computer Science, Data Science, AI/Machine Learning, Telecommunications Engineering, Applied Mathematics/Physics, or a related computational field. Technical Skills: • Strong programming skills in Python or R. • Solid foundation in Machine Learning and Deep Learning architectures. • Familiarity with IoT protocols, data integration pipelines, and handling heterogeneous datasets. • Familiarity with water networks modelling. • Knowledge of distributed computing frameworks and decentralized databases is a strong plus.

Requirements / 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. Candidates must also comply with all applicable eligibility requirements and regulations of the Marie Skłodowska-Curie Actions (MSCA) Doctoral Networks programme.

Requirements / required languages / language: ENGLISH

Requirements / required languages / language level: Good

Requirements / required languages / language: CATALAN

Requirements / required languages / language level: Basic

Requirements / required languages / language: SPANISH

Requirements / required languages / language level: Basic

Additional information / benefits: The planned remuneration for DN 2024 is as follows:

Salary: €33,667.67 gross per year Living allowance: €6,235.47 per year Family allowance: €5,796.35 gross per year + two secondments: • Secondment 1. 3-months secondment at VIT (supervised by Dr Castro-Gamma). The DC will receive a specialized training in efficient critical infrastructure (Digital Twins) and optimal operation with IHE, TUD, VIT and will conduct/receive a data collection/mentoring at VIT and BW. • Secondment 2. 2-months secondment at REBM (mentor Dr Chesneau) for testing and validating the findings.

Additional information / eligibility criteria: All candidates who cannot provide proof of the required academic qualification will be immediately excluded from the selection process. 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.

Threshold: 5 points.

The maximum score (10 points) will be distributed as follows: · 1 point for the required specialization. · 2 points for the required academic training. · 2 points for technical competencies. · 1 point for organizational competencies. · 3 points for professional experience. · 1 point for any aspect of the candidate’s professional profile that the selection committee considers particularly relevant. If the selection committee decides to include a personal interview as an additional step in the selection process, 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:

Maximum score: 5 points.

Threshold: 3 points.

The maximum score will be distributed as follows: · 2 points for suitability to the functional competencies of the position. · 2 points for the relevance of professional experience. · 1 point for any aspect of the candidate’s professional profile that the selection committee considers particularly relevant. Eligible candidates will be ranked from highest to lowest score, which will be the selection criterion.

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’ 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 information / comment: Contract duration: The employment contract will have a duration of 36 month starting by 1srt january 2027 Research field: Artificial Intelligence Required Languages: • English - C1 • Spanish or catalan will be taken into consideration

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.

Additional information / info website: https://websk.upc.edu/i3waters/

Additional information / info website: https://talenthub.upc.edu/en/jobs/r1/r1-jobs/investigador-a-en-formacio-per-realitzar-paradigmes-centralitzats-i-distribuits-per-a-sistemes-de-distribucio-daigua-a-lera-de-la-iot-codi-i3waters-dc11/investigador-a-en-formacio-per-realitzar-paradigmes-centralitzats-i-distribuits-per-a-sistemes-de-distribucio-daigua-a-lera-de-la-iot-codi-i3waters-dc11

Work location / nr job positions: 1

Work location / job organisation institute: Research Center for Supervision, Safety and Automatic Control (Universitat Politècnica de Catalunya)

Work location / job country: Spain

Work location / job state province: Barcelona

Work location / job city: Terrassa

Work location / job postal code: 08222

Work location / job street: Rambla Sant Nebridi, 22, Edifici Gaia

Hiring contact / organisation institute: Universitat Politècnica de Catalunya (UPC)- BarcelonaTECH

Hiring contact / organisation institute type: Higher Education Institute

Hiring contact / country: Spain

Hiring contact / city: Barcelona

Hiring contact / postal code: 08034

Hiring contact / street: C. Jordi Girona, 31

Hiring contact / e mail: i3waters.management@upc.edu

Hiring contact / e mail: ramon.perez@upc.edu

Hiring contact / e mail: personalinvestigador.sp@upc.edu

Hiring contact / website: https://www.upc.edu/

Hiring contact / website: https://cs2ac.upc.edu/en

Hiring contact / website: https://websk.upc.edu/i3waters

Hiring contact / phone: 34937398594

Application / how to apply: website

Application / application website: https://seuelectronica.upc.edu/en/procedures/call-for-recruitment-of-research-staff-in-training-predoctoral?set_language=en

EU funding / framework programme: Horizon Europe - MSCA

EU funding / cofund nr job position: 1

EU funding / sesam agreement number: 101227354

EU funding / job reference number: i3WaterS DC11

Research field / main research field: Computer science

Research field / sub research field: Other

Research field / main research field: Engineering

Research field / sub research field: Computer engineering

Researcher profile: First Stage Researcher (R1)

Positions: PhD Positions

Contract: Temporary

Job status: Full-time

Application deadline (as exported; timezone unverified): 2026-10-10T21:59:59