PhD Position in Digital Twins for Flood-Resilient Infrastructure

Job Details

• Faculty: Faculty of Civil Engineering and Geosciences (CEG), Department of Hydraulic Engineering, Flood Risk and Hydraulic Structures section.
• Location: Delft, the Netherlands.
• Project: FlooDT, an NWO-funded project led by TU Delft with ETH Zurich, Universitat Politècnica de Catalunya, Deltares and Rijkswaterstaat, supported by the TU Delft Digital Competence Centre.
• Contract: PhD, 4-year appointment, split into two contracts: an initial 1.5-year contract with a go/no-go assessment at 15 months, then 2.5 years if performance requirements are met.
• Hours: 32–40 hours per week (FTE 1.0).
• Salary: €3,204–€4,051 gross per month (year 1 to year 4), plus 8% holiday allowance and 8.3% end-of-year bonus, per the Collective Labour Agreement for Dutch Universities.
• Start date: March/April 2027.
• Closing date: 18 November 2026.
• Job ID: 3994.

Job Description

Flooding threatens infrastructure such as dikes and bridges, and current management tools struggle with complex, uncertain processes. Digital Twins could help by combining modelling, data assimilation, and machine learning with flood-risk models.

Your role:

• Develop Digital Twin modules, such as risk analysis, scenario modelling, and monitoring data processing.
• Develop hybrid physics-based and machine learning models for flood risk.
• Apply and validate these functions first on simplified infrastructure representations, then on real case studies.
• Implement the functions into end users’ platforms.
• Co-organise workshops and coordinate stakeholder engagement, such as meetings, presentations, and site visits.

Job Requirements

• MSc in Civil Engineering, Computer Science, Hydro-informatics, or a related discipline.
• Demonstrated experience in numerical modelling, hydrodynamic simulation, and data management.
• Scientific and/or practical knowledge of machine learning.
• Strong programming skills (for example Python, SQL, Java, PyTorch).
• Critical, creative, proactive research approach with strong problem-solving skills.
• Proven experience writing scientific reports and publications.
• Confidence in engaging with partners and stakeholders.
• Excellent written and spoken English.
• Non-academic internship experience is desirable (not required).

About TU Delft and the Faculty

• TU Delft focuses on energy, climate, digitalisation, AI, and smart mobility, with an international community of staff and students.
• CEG covers civil engineering, applied earth sciences, transport, water technology, and delta technology, with 28 research groups across seven departments.

Conditions of Employment

• Enrolment in the TU Delft Graduate School, with supervisors, a mentor, and a Doctoral Education Programme covering transferable, discipline-related, and research skills.
• Customisable compensation package, health insurance discounts, and a monthly work costs contribution.
• Flexible work schedules by arrangement.
• Relocation support through Coming to Delft Service, including settling-in events and a Dual Career Programme for accompanying partners.

Additional Information

• Contact for specific questions: Maria Pregnolato, m.pregnolato@tudelft.nl. General questions are not answered.
• Online interviews are planned for December, after the first selection.
• Interviewees will be asked for at least two references.

How to Apply

• Apply online only. Applications by email or post are not processed.
• Upload a CV (maximum 4 pages) and a cover letter (maximum 1 page) describing your motivation and qualifications.
• TU Delft requires English proficiency at a certain level. See the Graduate Schools Admission Requirements for details.
• TU Delft runs a knowledge security risk assessment in the final selection stages, based on information you provide. You will be informed if the outcome is negative.
• Do not contact TU Delft about unsolicited services.

More information and application: https://careers.tudelft.nl/job/Delft-PhD-Position-in-Digital-Twins-for-Flood-Resilient-Infrastructure-2628-CD/1375576057/