Job description
The Netherlands relies heavily on its dikes. However, current models do not fully explain how dikes collapse when seepage flows erode sand underneath a dike (i.e., Backward Erosion Piping). The Digital Dikes project is changing that — it aims to develop advanced digital models with varying degrees of detail, integrated into a flexible open-source tool, assimilating monitoring data to give probabilistic predictions. This framework can assess the probability (and severity) of pipe progression as a function of dike geometry, variability of subsurface properties, and hydraulic loads. The novel technology will be tested through real-world case studies, co-designed with industry, government, and international users. This will make accurate risk assessment and targeted dike reinforcement possible.
Digital Dikes is a prestigious and ambitious project funded by the Netherlands Organisation for Scientific Research (NWO), involving partners from the University of Twente (leading institution), the University of Utrecht, Eindhoven University of Technology, the University of Bologna, Deltares, and Delft University of Technology (TU Delft). The partners are supported by a large group of stakeholders, including water authorities, Rijkswaterstaat, STOWA, Dutch Flood Protection Programme, and international organisations.
This PhD position uses the Random Finite Element Method (RFEM) to investigate the role of soil spatial variability on the initiation and progression of backward erosion piping under dikes. RFEM links the finite element method for modelling geotechnical structure response with stochastic models of ground spatial variability, within a Monte Carlo framework to account for uncertainty in soil parameter values. The research includes the following components: (a) the development and validation of a 3D RFEM tool, which may be constrained and updated by measurement and monitoring data, for modelling groundwater flow and piping initiation/progression in heterogeneous soils; (b) the application of the developed tool for investigating the influence, on piping initiation, progression and extent, of the spatial variability of geological layering and spatial variability within layers; (c) the utilisation of RFEM results to develop, train and test a reliability-based surrogate model for practical risk assessments; (d) an investigation of design protocols for monitoring and measurement systems to reduce uncertainty and improve dike safety.
The project combines fundamental research with applied relevance. It will be carried out in the Geo-Engineering section of Delft University of Technology and involves collaboration with other partners within the Digital Dikes consortium. The project will benefit from a wide range of training activities, workshops, and dedicated sessions at international meetings, to foster scientific and transferable skills.
Job requirements
We are looking for a candidate with an MSc degree in Civil Engineering, Geosciences, or a related field. The candidate should have a strong background in numerical modelling and have a genuine interest and aptitude for the development, computer implementation, and application of numerical and probabilistic-based algorithms. A knowledge of machine learning techniques and soil mechanics would be an advantage. The candidate should have excellent computer programming skills, proficiency in verbal and written English, and experience with teamwork.
TU Delft (Delft University of Technology)
Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.
At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.
Challenge. Change. Impact!
Faculty of Civil Engineering and Geosciences
The Faculty of Civil Engineering & Geosciences (CEG) is committed to outstanding international research and education in the field of civil engineering, applied earth sciences, traffic and transport, water technology, and delta technology. Our research feeds into our educational programmes and covers societal challenges such as climate change, energy transition, resource availability, urbanisation and clean water. Our research projects are conducted in close cooperation with a wide range of research institutions. CEG is convinced of the importance of open science and supports its scientists in integrating open science in their research practice. The Faculty of CEG comprises 28 research groups in the following seven departments: Materials Mechanics Management & Design, Engineering Structures, Geoscience and Engineering, Geoscience and Remote Sensing, Transport & Planning, Hydraulic Engineering and Water Management.
Conditions of employment
Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.
Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from €3059 - €3881 gross per month, from the first year to the fourth year based on a fulltime contract (38 hours), plus 8% holiday allowance and an end-of-year bonus of 8.3%.
As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.
The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.
Will you need to relocate to the Netherlands for this job? TU Delft is committed to make your move as smooth as possible! The HR unit, Coming to Delft Service, offers information on their website to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands.
Additional information
For more information about this vacancy, please contact Prof. Dr. Michael A. Hicks, [email protected], or Dr. Zheng Guan, [email protected]
Application procedure
Are you interested in this vacancy? Please apply no later than 22 June 2026 upload the following documents:
- A motivation letter (max 2 pages).
- Your CV.
- Academic transcripts (BSc and MSc).
You can address your application to Michael Hicks.
Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements.
Please note:
- You can apply online. We will not process applications sent by email and/or post.
- As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed. The processing of personal data in the context of the risk assessment is carried out on the legal basis of the GDPR: performing a public task in the public interest. You can find more information about this assessment on our website about knowledge security.
- Please do not contact us for unsolicited services.
