In either of the two related PhD projects, you will be working on developing and applying so-called interpretable or eXplainable AI (XAI) technology for the prediction and management of either crowds or multi-modal traffic in networks, by capitalising on the vast amounts of heterogeneous data that have been collected.

The multi-modal network management project entails developing schemes for the short-term prediction of multi-modal network traffic flows as well as the development of AI-inspired (e.g., reinforcement learning) methods for the network-wide management of these networks that use these predictions. We expect that the developed methods will capitalise on current developments in traffic network theory, including, but not limited to, the (generalised) network fundamental diagram for multimodal traffic, decentralised network control schemes, and perimeter control approaches for large scale applications. The proposed methods are to be applied to a case in the Dutch city of Utrecht, in close cooperation with the firm Arane (www.arane.nl).

For the crowd risk assessment and management project, the methods to be developed aim to predict (short-term) and forecast (long-term) dynamics of crowds using heterogeneous sources of data, and subsequently assess and predict the risk of incidents or accidents, again using various sources of data (e.g., police reports, sentiments from video analysis or social data). The project will result in a pilot study for the The Hague area (i.c., Scheveningen), in close collaboration with the firm Argaleo (http://www.argaleo.nl).

These PhD projects are conducted at the Department of Transport and Planning (T&P) of the Delft University of Technology. T&P aims at top-level fundamental research that contributes to a more efficient and robust design and reliable operation of transport systems. T&P is composed of 11 research labs addressing various transport challenges. You will be part of the Artificial Intelligence for Mobility Lab (AIM Lab) as well as the Urban Mobility Observatory (UMO) lab. AIM lab develops innovative data-driven models and methods for evidence-based mobility planning and management to improve overall transport system performance - closely related to public transport, car traffic, and active modes. The UMO lab aims to design data collection systems and supporting methods (e.g., sensor network design, experimental design, sensor validation, data fusion).

The candidates we are looking for have:

• An MSc degree or equivalent in data science, computer science, and/or transportation engineering.
• Good programming skills.
• Sound and quantitative understanding of networked systems.
• Excellent interpersonal and communication skills.
• It is a plus if you have experience in machine learning.

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. 

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.

Fixed-term contract: 4 years.

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 € 2541 per month in the first year to € 3247 in the fourth year. 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 sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. For international applicants we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation.

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 Civil Engineering & 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 depletion, urbanisation and the availability of clean water, conducted  in close cooperation with a wide range of research institutions. CEG is convinced that Open Science helps to achieve our goals 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.