Are you a Master’s graduate with a strong background in hydroinformatics, water engineering, civil or environmental engineering, applied mathematics, operations research, or computer science? Are you interested in artificial intelligence, optimisation, hydraulic modelling, uncertainty analysis, digital twins, and intelligent water systems?

The IHE Delft Institute for Water Education is offering an exciting PhD Candidate position in Hydroinformatics as part of the Horizon Europe Marie Skłodowska-Curie Actions (MSCA) Doctoral Network i3WaterS – Intelligent, Innovative and Integrative Water Systems.

This four-year doctoral research opportunity is designed for an ambitious researcher who wants to contribute to the future of intelligent, resilient, sustainable, and data-driven drinking-water distribution systems.

The selected candidate will be based in Delft, the Netherlands, and will work within IHE Delft’s Hydroinformatics and Socio-Technical Innovation Department. The research will focus specifically on developing uncertainty-aware optimisation approaches that can help water utilities make better operational decisions when hydraulic models, operational data, water demand, and other inputs are uncertain.

The position combines academic research, advanced computational methods, artificial intelligence, optimisation, water-system modelling, international collaboration, and practical engagement with water utilities.

Opportunity Overview

The PhD candidate will undertake research within the Horizon Europe-funded i3WaterS Doctoral Network, which brings together universities, research institutions, technology developers, and water utilities.

The broader i3WaterS network will train 15 Doctoral Candidates in developing advanced approaches for intelligent water systems. The programme integrates:

• Monitoring data
• Expert knowledge
• Hydraulic models
• Water-quality models
• Digital twins
• Optimisation
• Artificial intelligence
• Machine learning
• Decision-support systems
• Uncertainty analysis
• Data-driven modelling

The goal is to develop innovative approaches that can help drinking-water distribution systems become more intelligent, resilient, efficient, and sustainable.

For this particular PhD project, the successful candidate will investigate how uncertainty can be explicitly incorporated into operational optimisation.

PhD Research Topic

Uncertainty-Aware Optimisation for Robust Water Distribution System Operation

Water distribution systems are complex infrastructure networks. Their operation depends on many variables, including water demand, hydraulic conditions, network characteristics, operational decisions, and information obtained from monitoring systems.

However, these variables are not always known with complete certainty.

Hydraulic models may contain uncertainties, operational data may be incomplete or inaccurate, and water demand can fluctuate significantly. Consequently, an operational decision that appears optimal under one set of assumptions may not perform as expected when actual conditions differ.

This PhD research will address this challenge by developing uncertainty-aware, model-based, multi-objective optimisation methodologies for drinking-water distribution systems.

The research will explicitly account for uncertainty in hydraulic models and operational data and investigate how different sources of uncertainty influence operational decisions.

An important part of the research will involve identifying which uncertainties are significant enough to justify further investigation or additional information gathering.

The project will therefore make use of Value of Information (VoI) concepts to determine which uncertainty sources are worth resolving and which may not materially affect decisions.

The ultimate goal is to advance computational methods that enable robust and potentially real-time operational optimisation for water distribution systems.

Main Research Objectives

The successful PhD candidate will be expected to contribute to several major research objectives.

1. Identify Important Sources of Uncertainty

The research will develop methodologies and reproducible computational tools for determining which uncertainty sources have a meaningful impact on operational decisions.

Not every uncertainty within a water distribution system will necessarily need to be resolved.

The candidate will therefore investigate how uncertainties can be assessed and prioritised, including through Value of Information approaches.

This can help water utilities focus their resources on collecting, improving, or resolving information that has the greatest influence on decision-making.

2. Develop Robust Optimisation Methods

The project will develop methods for optimising water-distribution-system operations while accounting for uncertain inputs.

Rather than assuming that all model parameters and operational conditions are perfectly known, the research will investigate optimisation approaches capable of producing decisions that remain effective under uncertainty.

This will involve robust and potentially stochastic multi-objective optimisation approaches.

3. Develop Reproducible Code

An important expected outcome of the PhD will be the development of reproducible research methodologies and software.

The candidate is expected to produce:

• Reproducible code for identifying influential uncertainty sources
• Computational approaches for uncertainty-aware decision-making
• Code for robust optimisation of water distribution system operations
• Methods that can potentially support real-time operational decision-making

Reproducibility will be important because the resulting methodologies should be useful for future research and potentially transferable to practical water-management applications.

4. Validate the Research Using a Real Utility Case

The research will not remain purely theoretical.

The developed methodologies will be validated using a real water utility case.

The candidate will assess how the proposed methods perform under realistic operational conditions and evaluate their potential benefits and limitations.

The validation will include an assessment of:

• Operational performance improvements
• Robustness of decisions
• Practical applicability
• Limitations of the proposed methods
• Effects of uncertainty on operational outcomes

This real-world component provides an opportunity for the doctoral research to connect advanced computational research with practical water-utility challenges.

Expected Results of the PhD

The project identifies three major expected outcomes.

Expected Result 1: Uncertainty Identification Methodology

The candidate will develop a methodology and reproducible code capable of identifying uncertainty sources that materially affect operational decisions.

Expected Result 2: Robust Optimisation Methodology

The candidate will develop a methodology and associated code for robust optimisation of water-distribution-system operations under uncertain inputs.

Expected Result 3: Real-World Validation

The developed research will be tested using a real utility case, with an assessment of performance improvements and limitations.

Together, these outputs are expected to contribute to more reliable and intelligent operational decision-making within drinking-water distribution systems.

Host Institution: IHE Delft Institute for Water Education

The selected candidate will be hosted by the Hydroinformatics and Socio-Technical Innovation Department at IHE Delft in Delft, Netherlands.

IHE Delft is an international institution specialising in water education, research, and capacity development.

The doctoral researcher will work within an interdisciplinary environment connecting water engineering, hydroinformatics, data science, artificial intelligence, modelling, optimisation, and socio-technical innovation.

The position provides an opportunity to conduct doctoral research while collaborating with academic researchers, water-sector professionals, technology developers, and other doctoral researchers within the i3WaterS network.

PhD Supervisory Team

The doctoral candidate will benefit from a supervisory team involving academic and industry expertise.

Main Supervisor: Associate Professor Leonardo Alfonso

Associate Professor Leonardo Alfonso of IHE Delft will serve as the main supervisor.

Co-Supervisor: Dr Oscar Coronado Hernandez

Dr Oscar Coronado Hernandez from the University of Cartagena will serve as co-supervisor.

Industrial Mentor: Dr Claudia Quintiliani

Dr Claudia Quintiliani from Brabant Water will act as the industrial mentor.

This combination of academic and industry supervision is particularly relevant because the research is intended to address both methodological research questions and practical water-utility challenges.

International Training and Mobility

One of the major advantages of this opportunity is participation in the i3WaterS International Doctoral School.

The Doctoral School is organised across six chapters in:

1. Barcelona
2. Dublin
3. Bordeaux
4. Delft
5. Brussels
6. Newcastle

The international training programme is designed to provide doctoral researchers with technical, research, professional, and transferable skills.

Training areas include:

• Artificial intelligence and machine learning
• Explainable AI
• Trustworthy AI
• Knowledge representation
• Multi-agent systems
• Intelligent decision-support systems
• Digital twins
• Smart water systems
• Innovation
• Entrepreneurship
• Scientific communication
• Transferable professional skills

This means the successful candidate will not only work on their individual PhD research but will also participate in an international training environment with researchers from different institutions and countries.

International Secondments

The doctoral programme includes international secondments that will provide additional practical and research experience.

University of Cartagena Secondment

A three-month secondment at the University of Cartagena (UC) is planned from project month 21.

The secondment will focus on:

• Water-demand forecasting
• Optimal water-system operation
• Specialised training
• Research collaboration

The candidate will also collaborate with Aguas de Cartagena (AC) during this period.

This secondment will provide exposure to water-demand forecasting and operational challenges in a different geographical and institutional context.

Cetaqua Secondment

A second secondment lasting two months is planned at Cetaqua (CET) from project month 34.

The purpose of this secondment will be to:

• Test the research findings
• Validate the developed approaches
• Collaborate with specialists
• Assess the practical applicability of the research

The timing of either secondment may be adjusted in consultation with the supervisory team and host organisations.

Responsibilities of the PhD Candidate

The successful applicant will have a broad range of academic, research, technical, and collaborative responsibilities.

Research and Method Development

The candidate will:

• Plan and develop the research methodology.
• Implement the methods and tools identified in the project objectives.
• Follow developments in state-of-the-art decision-making under uncertainty.
• Investigate robust multi-objective optimisation approaches.
• Apply these approaches to drinking-water distribution systems.
• Develop computational methods for operational decision-making.

Project Participation

The researcher will also contribute to the wider i3WaterS project by participating in:

• Project deliverables
• Technical reports
• Research meetings
• Network-wide activities
• Collaborative research activities

Academic Publications

The candidate will be expected to disseminate research findings through academic channels.

This includes:

• Publishing research in peer-reviewed journals
• Presenting findings at national conferences
• Presenting at international conferences
• Participating in symposia
• Communicating research results to academic and professional audiences

International Collaboration

The candidate will actively participate in:

• The International Doctoral School
• International secondments
• Collaborative research activities
• Academic partnerships
• Non-academic partner activities

MSc Thesis Support

Where appropriate, the doctoral candidate may also support or mentor MSc thesis projects related to the doctoral research.

PhD Thesis

The ultimate responsibility will be to prepare and successfully defend a doctoral thesis within the appointment period.

Required Qualifications

Applicants must meet the academic and technical requirements of the position.

Master’s Degree

Applicants must hold a Master’s degree with strong academic results in one of the following fields:

• Hydroinformatics
• Civil engineering
• Environmental engineering
• Water engineering
• Applied mathematics
• Operations research
• Computer science
• A closely related field

Applicants whose Master’s degree is in another discipline may potentially be considered if their academic and technical background is closely aligned with the requirements of the research project.

Hydraulics and Hydraulic Modelling

Applicants should have strong knowledge of:

• Hydraulics
• Hydraulic modelling
• Drinking-water distribution systems

This is a particularly important requirement because the PhD focuses directly on the optimisation and operation of water-distribution networks.

Candidates should therefore be comfortable working with the technical principles behind water-distribution-system modelling.

Optimisation

Applicants should have knowledge of optimisation.

Experience with multi-objective optimisation is particularly desirable.

Knowledge or interest in the following areas will also be valuable:

• Robust optimisation
• Stochastic optimisation
• Decision-making under uncertainty
• Mathematical optimisation
• Computational optimisation

Programming

Applicants are expected to have programming experience in Python.

Experience with optimisation libraries is highly desirable.

Knowledge of water-network modelling software is also considered highly desirable.

Data Science and Artificial Intelligence

Experience in the following areas is an advantage:

• Data science
• Machine learning
• Uncertainty quantification
• Value of Information methods
• Artificial intelligence
• Data-driven modelling

These skills can strengthen an applicant’s profile, particularly because the wider i3WaterS network focuses on intelligent and AI-enabled water systems.

English Language Requirements

Applicants must demonstrate proficiency in written and spoken English.

The position also requires the ability to independently write academic texts in English.

This is important because the candidate will be expected to produce:

• Research papers
• Technical reports
• PhD research documentation
• Conference presentations
• The doctoral thesis
• Other academic and project-related materials

Personal and Professional Competencies

In addition to academic qualifications, IHE Delft is looking for a candidate with a collaborative and proactive attitude.

The ideal candidate should demonstrate:

• Ability to conduct independent research
• Proactive working style
• Strong collaboration skills
• Interest in multidisciplinary research
• Ability to work in multicultural environments
• Willingness to collaborate with academic and non-academic partners
• Strong written communication
• Strong analytical thinking
• Capacity to learn advanced technical methods

Because the project involves multiple universities, research institutions, technology developers, and water utilities, the ability to work effectively with people from different professional and cultural backgrounds will be important.

MSCA Doctoral Network Eligibility

In addition to the academic requirements, applicants must satisfy the eligibility conditions applicable to Marie Skłodowska-Curie Actions Doctoral Networks.

You Must Not Already Hold a Doctoral Degree

At the date of recruitment, the applicant must be a Doctoral Candidate.

The candidate must not already hold a doctoral degree and must not have defended a doctoral thesis.

This means the position is intended for researchers who are entering or undertaking their doctoral research rather than individuals who have already completed a PhD.

MSCA Mobility Rule

The MSCA mobility rule also applies.

During the 36 months immediately before the recruitment date, the applicant must not have:

• Resided in the Netherlands for more than 12 months; or
• Carried out their main activity in the Netherlands for more than 12 months.

Main activity includes activities such as work or studies.

Certain periods are excluded from this calculation, including:

• Compulsory national service
• Time spent obtaining refugee status under the Geneva Convention

Applicants should carefully verify their personal mobility history before applying because satisfying the MSCA mobility rule is an essential eligibility condition.

Employment Duration

This is a 48-month, four-year PhD position.

The position is based on a working schedule of 38 hours per week.

The expectation is that the candidate will complete and successfully defend the PhD thesis within the four-year appointment period.

Initial Contract

The initial employment contract will be for 18 months.

During the first year, a go/no-go decision will be made.

This decision will be based on a detailed PhD research proposal developed by the candidate.

Following this assessment, the contract may be extended if the candidate successfully meets the required expectations.

Salary and Employment Conditions

Employment at IHE Delft will be according to the Collective Labour Agreement for Dutch Universities, under scale P.

The appointment also includes entry into the Netherlands’ Civil Service Pension Fund (ABP).

The final remuneration package will be determined according to:

• IHE Delft employment conditions
• Applicable MSCA Doctoral Network allowances

Applicants should therefore understand that the position is not simply an academic study opportunity but a formal employment-based doctoral appointment with associated employment conditions.

Expected Start Date

The expected contract starting date is:

1 January 2027

Applicants should be prepared to commence the doctoral appointment around this date if selected.

Application Deadline

The application deadline is:

20 September 2026 at 23:59 CEST (Brussels time)

Applicants are strongly encouraged to submit their applications before the deadline rather than waiting until the final hours.

Documents Required

Applicants must submit their application in English.

The application should include the following documents:

1. Curriculum Vitae

Applicants must provide an up-to-date CV detailing their:

• Academic background
• Research experience
• Technical skills
• Programming experience
• Professional experience
• Publications, where applicable
• Relevant projects
• Other qualifications relevant to the position

Qualifications, experience, and other claims included in the CV should be supported by appropriate evidence.

2. Motivation Letter

The motivation letter should explain why the applicant is interested in:

• The PhD project
• Hydroinformatics
• Water-distribution-system optimisation
• Uncertainty-aware decision-making
• IHE Delft
• The i3WaterS Doctoral Network

It should also demonstrate how the applicant’s academic background, technical skills, research interests, and career goals align with the position.

3. MSc Thesis Abstract

Applicants must submit an abstract of their Master’s thesis.

This provides an opportunity to demonstrate previous research experience and show how their Master’s research relates to the PhD project.

Applicants should clearly communicate the research problem, methodology, key findings, and relevance of their MSc thesis.

4. Two Referees

Applicants must provide the names of two contactable referees.

Applicants should select referees who can provide meaningful information about their:

• Academic performance
• Research abilities
• Technical skills
• Professional conduct
• Capacity for independent work
• Suitability for doctoral research

How to Apply

Applications must be submitted in English through the official application system HERE using the Apply button associated with the vacancy.

Applications submitted by email will not be considered.

Applicants can upload the required documents as PDF files through the Motivation and CV upload section.

Therefore, candidates should ensure that all required application documents are prepared in PDF format before beginning the application process.

Visit the IHE Delft Institute for Water Education website HERE for more information

Selection Process

IHE Delft will follow a structured selection process.

Stage 1: Formal Eligibility Check

Applications will first be checked to determine whether applicants meet the formal eligibility requirements.

This includes checking requirements related to:

• Doctoral-candidate status
• Academic qualifications
• MSCA eligibility
• Mobility requirements
• Application documentation

Only candidates who satisfy the formal requirements will proceed to the next stage.

Stage 2: CV Assessment

Eligible CVs will be assessed according to several criteria.

These include:

• Required specialisation
• Academic training
• Technical competencies
• Organisational competencies
• Professional experience
• Overall suitability for the position

Candidates must obtain at least 5 out of 10 in the CV assessment to potentially be invited to an interview.

Stage 3: Online Interview

Candidates who successfully pass the CV assessment may be invited to an online interview.

The interview will assess:

• Functional suitability
• Relevance of professional experience
• Overall professional profile

The minimum interview score is 3 out of 5.

Stage 4: Final Ranking

Eligible candidates will ultimately be ranked according to the final assessment.

Interview dates and arrangements will be communicated to shortlisted applicants in advance by email.

Diversity and Equal Opportunity

IHE Delft states that it follows an open recruitment procedure that respects diversity and provides equal opportunity to applicants from all backgrounds.

There is no specific race, nationality, or continental restriction stated in the vacancy.

However, applicants must satisfy the academic, doctoral, technical, English-language, and MSCA mobility requirements.

Who Should Apply?

This PhD position may be particularly suitable for candidates who have recently completed, or are completing, a Master’s degree and want to pursue a research career at the intersection of water systems and advanced computational methods.

Strong candidates may come from backgrounds such as:

• Hydroinformatics
• Civil engineering
• Environmental engineering
• Water resources engineering
• Water engineering
• Applied mathematics
• Operations research
• Computer science
• Related engineering or quantitative disciplines

The strongest applicants will likely be those who can demonstrate a combination of relevant academic training and technical skills.

For example, a candidate with water-system modelling experience combined with Python programming and optimisation knowledge could be particularly well aligned with the project.

Similarly, applicants with experience in machine learning, uncertainty quantification, data science, or Value of Information methods may have an additional advantage.

Why This PhD Opportunity Is Valuable

This position offers more than a conventional doctoral research experience.

The project sits at the intersection of several rapidly developing fields:

• Water engineering
• Hydroinformatics
• Artificial intelligence
• Machine learning
• Optimisation
• Uncertainty quantification
• Digital twins
• Data science
• Decision-support systems
• Smart water infrastructure

The successful candidate will have the opportunity to develop expertise in technologies and methodologies that are increasingly relevant to the digital transformation of water utilities.

The international structure of the i3WaterS Doctoral Network also provides opportunities to interact with researchers and professionals across multiple European locations and partner institutions.

Key Benefits and Opportunities

The position provides several important professional and academic opportunities, including:

• A four-year doctoral research position.
• Employment at IHE Delft in the Netherlands.
• Research within a Horizon Europe MSCA Doctoral Network.
• International doctoral training.
• Participation in the i3WaterS International Doctoral School.
• Training in AI and machine learning.
• Training in explainable and trustworthy AI.
• Exposure to digital twins and smart water systems.
• Research in robust and multi-objective optimisation.
• Experience with decision-making under uncertainty.
• Opportunities for academic publication.
• Opportunities to present research at conferences and symposia.
• International research collaboration.
• A three-month secondment at the University of Cartagena.
• Collaboration with Aguas de Cartagena.
• A two-month secondment at Cetaqua.
• Exposure to real-world water utility challenges.
• Opportunities to support MSc research projects.
• Academic and industrial supervision.
• A pathway toward completing and defending a PhD.

Important Dates

Item	Date
Publication date	25 August 2026
Application deadline	20 September 2026
Deadline time	23:59 CEST (Brussels time)
Expected contract start	1 January 2027
Contract duration	48 months
Initial contract	18 months
Working hours	38 hours per week
University of Cartagena secondment	Three months, planned from project month 21
Cetaqua secondment	Two months, planned from project month 34

Contact Information

Applicants who require additional information about the research project can contact:

Associate Professor Leonardo Alfonso Segura

IHE Delft Institute for Water Education

Email: l.alfonso@un-ihe.org

Telephone: +31 15 215 2394

Potential applicants with technical questions about the research topic may find it useful to contact the project supervisor before applying, particularly if they need clarification about the research scope or suitability of their academic background.

Application Tips for Prospective Candidates

Although the vacancy provides specific application requirements, applicants can strengthen their applications by carefully demonstrating how their background matches the project.

Tip 1: Highlight Relevant Technical Skills

Do not simply list technical skills in your CV.

Where possible, demonstrate how you have used them.

For example, if you have experience with Python, optimisation, hydraulic modelling, machine learning, or data analysis, describe the projects in which you applied those skills.

Tip 2: Connect Your MSc Research to the PhD

The MSc thesis abstract is an important component of the application.

Clearly explain your research question, methodology, results, and contribution.

If your MSc research relates to water systems, modelling, optimisation, data science, engineering, or computational methods, make the connection clear.

Tip 3: Demonstrate Research Potential

This is a doctoral research position, so the selection committee will be interested not only in what you have studied but also in your potential to conduct independent research.

Highlight evidence such as:

• Research projects
• Thesis work
• Publications
• Conference presentations
• Data analysis projects
• Programming projects
• Research assistant experience
• Technical reports

Tip 4: Address the Motivation Letter Carefully

A strong motivation letter should go beyond saying that you want to study for a PhD.

Explain why this specific research project interests you and how your background prepares you to contribute to it.

You should also demonstrate an understanding of the research problem involving uncertainty-aware optimisation and water-distribution-system operation.

Tip 5: Verify MSCA Eligibility Early

Applicants should carefully check the doctoral-candidate and mobility requirements before investing significant time in the application.

In particular, review your residence and main-activity history in the Netherlands during the 36 months immediately preceding recruitment.

Tip 6: Prepare Your Referees

Contact your two referees in advance.

Make sure they are aware that they may be contacted and that they understand the type of PhD position for which you are applying.

Tip 7: Submit Before the Deadline

Do not wait until the final hours to upload your documents.

The deadline is 20 September 2026 at 23:59 CEST (Brussels time), so applicants should allow sufficient time to prepare PDFs, review their application, and complete the online submission.

Final Thoughts

The PhD Candidate in Hydroinformatics – Uncertainty-Aware Optimisation for Robust Water Distribution System Operation at IHE Delft represents an opportunity for an aspiring researcher to work on an important challenge facing modern water systems.

As drinking-water utilities increasingly adopt digital technologies, data-driven decision-making, artificial intelligence, digital twins, and advanced optimisation, the ability to make reliable operational decisions despite uncertainty is becoming increasingly important.

This doctoral project addresses that challenge by combining hydraulic modelling, optimisation, uncertainty analysis, artificial intelligence, data, and real-world water-utility applications.

The successful candidate will join the international i3WaterS Doctoral Network and receive multidisciplinary training while collaborating with universities, research institutions, technology developers, and water utilities.

The programme also offers international mobility through training across European locations and research secondments at the University of Cartagena and Cetaqua.

For candidates with the appropriate Master’s degree, strong academic performance, relevant technical knowledge, Python programming experience, and a genuine interest in water systems and computational optimisation, this could be a strong opportunity to develop an international research career in hydroinformatics and intelligent water management.

Interested applicants should carefully review the eligibility requirements, prepare their CV, motivation letter, MSc thesis abstract, and two referee contacts, and submit the complete application through the official IHE Delft application system.

Application deadline: 20 September 2026 at 23:59 CEST (Brussels time).

Expected start date: 1 January 2027.

For more PHD programs visit the OFY Website HERE