Reshape how cities plan and operate multimodal transport systems, from real-time fleet management to long-term infrastructure expansion, under deep uncertainty in a new ERC-funded project at TU Delft.
Job description
The scientific challenge
Urban transport systems generate ever-growing data streams, yet they continue to fail during disruptions. One key reason is that short-term operations and long-term planning are designed in silos. As a result, supply and demand adjustments occur out of sync, leading to congestion, inefficiencies, and service breakdowns.
The ERC consolidator project TRANSFORM addresses this gap by developing a unified framework for resilient multimodal systems under uncertainty. The project reframes multimodal mobility as a coupled system with three interacting players, mobility service suppliers, infrastructure operators, and users whose decisions and reactions unfold on different time scales. What makes TRANSFORM distinctive is the way it fuses dynamic uncertainty modeling, behaviorally informed demand management, and iterative optimization across multiple decision layers into one coherent methodology.
Your Research Role
We are recruiting two PhD candidates, each focusing on a different but closely connected layer of this challenge.
PhD Position 1: Short-Term Multimodal Transport Planning under Uncertainty
This position focuses on operational decision-making in dynamic and disrupted environments.
You will:
- Develop next-generation short-term multimodal supply management models under deep uncertainty
- Integrate estimation and combinatorial optimization for large-scale fleet scheduling and service coordination
- Design AI-driven, tractable optimization methods for real-time decision support
- Develop scalable algorithms suitable for high-dimensional, capacity-constrained transport networks
This role would be a great fit for you if you have strong foundations in machine learning (for example causal inference or predictive modelling) and an interest in combinatorial optimization, or vice versa. Experience with simulation modelling is a plus.
PhD Position 2: Long-Term Multimodal Transport Planning under Uncertainty
This position focuses on strategic planning and infrastructure adaptation.
You will:
- Develop robust network expansion and adaptation models under deep and structural uncertainty
- Design new uncertainty quantification approaches for unobserved, heavy-tailed, and cascading disruption effects
- Integrate causal reasoning into large-scale combinatorial optimization for infrastructure planning
- Deliver methods that are both scientifically novel and deployable in real-world strategic planning contexts
This role would be a great fit for you if you have strong foundations in AI-driven modelling and large-scale optimization, and an interest in uncertainty modelling and strategic systems design, or vice versa.
Where you will work
Your home base will be the SUM Lab in the Department of Transport & Planning (T&P) within the Faculty of Civil Engineering and Geosciences. Our diverse team of researchers, project managers, and professors shares the ambition to create smart, sustainable, and equitable mobility systems. T&P consists of 12 collaborative labs applying advanced technologies such as sensing, data analytics, modelling, and AI to turn scientific research into real-world impact. You will work closely with domain experts Yanan Xin, Ludovic Leclercq, Yousef Maknoon and Oded Cats, and collaborate with fellow PhD colleagues and researchers across behavioral modelling, optimization, and transport systems analysis.
The position is embedded in a prestigious ERC consolidator grant, offering strong scientific visibility and opportunities for international collaboration.
Job requirements
- A Master's degree in a relevant field, i.e. Operations research, Applied mathematics, Machine Learning or Computer science. Engineering degree with strong methodological backgrounds is considered as well.
- Strong background in machine learning (e.g., predictive modelling, causal inference, or uncertainty quantification) and/or combinatorial optimization (mathematical modelling, decomposition methods, heuristics, metaheuristic).
- Advanced programming skills (e.g. Python, C++ or Java).
- Ability to work both in a project team, but also independently and take leadership and responsibility for research tasks.
- Interest in interdisciplinary collaboration and contributing to teaching activities.
- Excellent communication skills in English, both written and oral.
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.
Click here to go to the website of the Faculty of Civil Engineering & Geosciences.
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 Dr. Shadi Sharif Azadeh, email: s.sharifazadeh@tudelft.nl, stating the vacancy title and code in the email title.
Application procedure
Are you interested in this vacancy? Please apply no later than 1 April 2026 via the application button and upload the following documents:
You can address your application to Shadi Sharif Azadeh.
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.
