Doctoral researcher in optimization for robust railway timetables

Despite the excellent quality of public transport systems in Switzerland, the railway system needs to increase its performance (quality, for instance, travel time, and delays) and capacity (amount of services run) and attract more travellers to match the ambitious targets from policy and environmental goals. One key aspect of traditional railway transport systems is their plan, which is based on predetermined routes, lines, and scheduled times, with little possibility of adjusting to unplanned and unexpected circumstances. On the other hand, delays and disruption might affect many services throughout a network by means of propagation. The project focuses on timetable planning that is able to minimize delays and their impacts.

To do so, large-scale optimisation addresses the railway timetabling problem. Typically Mixed Integer Linear Programming approaches are used, which are mathematically complex, and with some limits, when modelling real-life complexity. Incorporating robustness against delays is an additional important aspect. This project assumes that we are able to quantify how small delays develop and propagate throughout the network; how larger disruptions develop and propagate in the network. Given this, we want to determine robust timetables, with suitable choice of buffers and running time reserves. Those timetables, under delays, are able to perform quantitatively better (i.e. less delays, fewer larger delays,...). 

This position will be available, with an ideal starting date between August 2026 and February 2027, or further upon agreement; the planned duration of the initial contract is 18 months, after which an aptitude colloquium will determine the further continuation of the doctoral project. The total doctoral project is expected to be finished in 4 years in total.

Project background

The focus of this project is to understand how different timetables result in complex dynamics as response to external events (small delays, larger disruptions). The scientific challenge involves integrating those dynamics into existing timetabling models, to identify those timetables that are actually better, under delays. This research targets improvement of timetable planning models, adjusting the amount and placement of buffers, and reserve times.

The project is designed in collaboration with industry player operating as railway infrastructure manager. The project bases on available solvers for non-periodic timetabling, which include MILP and Logic-Based Benders-Decomposition approaches. This research is carried out within an international cooperation with the Complex Systems group at Utrecht University, in the Netherlands.

Job description

• establish and use mathematical models for large-scale timetabling scheduling, with constraints on vehicles, crew, and infrastructure, able to address placement of buffers
• design and implement a simulation-optimization view to evaluate tentative solutions, considering estimated delay dynamics and possible degrees of rescheduling, to improve proactively and reactively the robustness against small and large delays.
• quantitatively understand the usefulness of the suggested decision, estimate its sensitivity to the considered assumptions; and compared to the typical reaction in real life

Profile

Ideally, you have (or are about to receive) a Masters’ degree in transport sciences, management/ decision sciences, econometrics, mathematics, statistics, computer science, physics or related fields. Your research track is consistent and shows a track record, or clear potential, for analysing, modelling, control, and optimisation of transport systems. You are highly motivated and self-driven, with a clear research vision, academic ambition, and excellent communication and writing skills (fluent spoken and written English is mandatory). Moreover, the following skills are expected of a promising candidate:

• Computer science and ability to program independently complex software
• Ability to model and work with algorithmic design, existing software and data provided by industrial partners
• Knowledge of mathematical optimisation (MILP, IP, LP) and/or control sciences
• Team working and communication skills
• Knowledge of German or similar languages is not required but is a plus

You enjoy working in an interactive international environment with doctoral students, post-docs and senior scientists, referring continuously to practical problems and solutions. 

We offer

You can look forward to an exciting working environment in a dynamic research group on transport systems, with large diversity in background and culture.

We expect active interaction in a group, with industrial players, and the international partners.

We are actively committed to a sustainable and climate-neutral university. You will also have access to the vast training program of ETH, and numerous benefits, such as public transport season tickets and car sharing, a wide range of sports offered by the ASVZ, childcare and attractive pension benefits.

We value diversity and sustainability

In line with our values , ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish. Sustainability is a core value for us – we are consistently working towards a climate-neutral future .

About ETH Zürich

ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.

The selection will be based on a multi-step application process. Firstly, applications will have to be submitted online, with the following documents submitted before 06. July 2026:

• a motivation letter describing how the experience and motivation fit the profile sketched in this call,
• a CV with a list of publications,
• diploma copies,
• one reference letter

After a first selection, potential candidates will be contacted for a final selection, which will be based on the candidates’ qualifications as well as on a personal interview with the supervisors. We strive to implement equal opportunity at hiring. 

For further information about the institute and the group, please visit our website . Questions regarding the position should be directed to Prof. Dr. Francesco Corman by email E-Mail auf jobs.nzz.ch ansehen (no applications).

Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

We would like to point out that the pre-selection is carried out by the responsible recruiters and not by artificial intelligence.