SORTEDMOBILITY will develop and assess concepts, models and algorithms to enable self-organizing railway operations, whereby intelligent trains autonomously participate in the traffic management. The aim is to improve flexibility, capacity and resilience of the railway system as a mobility backbone, to accomplish an efficient and demand-aware urban and interurban rail mobility growth. The assessment will be performed thanks to a holistic integrated approach which relies on advanced rail traffic simulation platforms developed in the project. The research will be performed in partnership with an international consortium of prominent universities and railway companies.

The PhD will be investigating models to simulate concepts of self-organising railway operations where autonomous trains could cooperate with each other by e.g. forming connected platoons or negotiate rescheduling/rerouting decisions at interlocking areas to maximise capacity and service performances. Research activities will mainly focus on the simulation of train operations under next-generation signalling systems such as Moving Block and Virtual Coupling and will include an impact assessment of self-organising services on various performance indicators.

The PhD candidate will specifically be involved in:

• Defining operational principles for flexible and self-organising railway operations.
• Developing simulation models to analyse dynamics and interactions of self-organising railway traffic under various signalling systems.
• Connecting self-organising decision making and passenger assignment methods to the EGTRAIN rail traffic simulation platform.
• Assessing impacts of self-organising railway traffic on real case studies.

The candidate has preferably an MSc in Engineering, Mathematics, Computer Science or similar scientific domain. Necessary requirements are:

• Acquaintance with railway operations.
• Background in mathematical modelling with experience in software/algorithm development.
• Good programming skills in .NET languages (preferably C++), and/or other programming languages.

• If your mother language is not English and you do not hold a degree from an institution in which English is the language of instruction, you must submit proof of English proficiency from either TOEFL (minimum total score of 100) or IELTS (minimum total score of 7.0). Proof of English language proficiency certificates older than two years are not accepted.

Knowledge of data management, software integration methods (e.g. API, AMQP, DDS middleware), statistical techniques, and traffic simulation tools (e.g. RailSys, VISSIM, OpenTrack) are an advantage.

In general, the candidate shall be open to work in a team within an interactive and stimulating environment. Advanced problem-solving skills and a prominent interest in contributing to scientific research are essential elements to the position.Proactiveness, independence and reliability in effectively and timely delivering tasks are a fundamental prerequisite for this position. Enthusiasm and passion for the railways are very valuable factors for the candidate given that the PhD will be performed in the railway sector.

Fixed-term contract: 4 Years.

TU Delft offers PhD-candidates a 4-year contract, with an official go/no go progress assessment after one year. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2395 per month in the first year to € 3061 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 and aim to be as inclusive as possible (see our Code of Conduct). Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale.

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.

The Digital Rail Traffic Lab (DRTLab) performs research to develop innovative concepts, models and methods for advanced analysis and evaluation of railway operations, effective railway transport planning, and efficient railway traffic management and train control. Key focus is on intelligent decision support and automation using optimization, data analytics and simulation to realize resilient railway traffic systems. The DRTLab is part of the Department of Transport & Planning which aims to deliver top scientific research and world class education to create an efficient, sustainable and resilient transportation system. The Department is composed of a total of 11 multi-disciplinary research labs addressing several hot transportation challenges to solve congestion, improving safety and reliability while reducing environmental impacts.

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