15/04/2021
The Human Resources Strategy for Researchers

PhD Position Flexible Railway Timetabling with Demand-Driven Train Service Variations

This job offer has expired


  • ORGANISATION/COMPANY
    Delft University of Technology (TU Delft)
  • RESEARCH FIELD
    Technology
  • RESEARCHER PROFILE
    First Stage Researcher (R1)
  • APPLICATION DEADLINE
    01/06/2021 01:59 - Europe/Brussels
  • LOCATION
    Netherlands › Delft
  • TYPE OF CONTRACT
    Temporary
  • HOURS PER WEEK
    40.0

OFFER DESCRIPTION

A key challenge for railway transport is to guarantee an attractive overall offer that is flexible in adapting capacity to meet both short-term variations and long-term trends in travel demand. In the Netherlands and many other European countries, passenger trains operate a fixed line plan with a regular interval throughout the day for each day of the week. However, there is an increasing interest in more flexible timetables that are better aligned with distinctive passenger flow patterns over the day or between days. For instance, commuter and leisure travels differ often in destination like business districts versus city centres. The COVID-19 pandemic clearly demonstrates how passenger demand dynamically evolves depending on government restrictions. Among the long-term behavioural effects of this pandemic, it is expected that more people will continue working from home with a preference for certain days.

In this PhD research you will be developing mathematical models to compute railway timetables that are flexible to variations in travel demand patterns. You will analyse passenger travel data to derive structural variations in passenger routes and departure times over the week. For the long term, you will apply stated preference methods to predict structural variations in future passenger behaviour. From the identified distinctive demand patterns you will derive homogeneous timetable periods with train service variations that may vary from small variations of a basic hour pattern to large changes in the line plan in certain areas and periods. Ultimately, you will develop a flexible railway timetable optimization problem to compute conflict-free multi-periodic railway timetables with service variations over homogeneous periods. This optimization problem will integrate elements from line planning, railway timetabling and passenger routing. Finally, you will solve flexible timetable problems for real-world cases from Netherlands railways.

This PhD project is a collaboration between the Department of Transport & Planning (T&P) of Delft University of Technology, and the Department Performance management & Innovation (PI) of Netherlands Railways (NS). You will be part of both the Digital Rail Traffic Lab (DRTLab) and the Smart Public Transport Lab (SPTL) at T&P, and also work in the Department PI at NS for one day per week. 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. The DRTLab develops innovative models and methods for railway transport planning, railway traffic management and train control to improve overall railway transport system performance. The SPTL develops new solutions and methods for public transport planning, operations and management

More Information

Benefits

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.

Selection process

You can apply to this PhD position until May 31, 2021. To apply, please submit your motivation letter (addressed to Prof. Rob Goverde), a detailed CV, BSc and MSc transcripts, and an abstract of your MSc thesis (one-page, in English).

  • You can apply online. We will not process applications sent by email and/or post.
  • A pre-Employment screening can be part of the selection procedure.
  • Acquisition in response to this vacancy is not appreciated.

Additional comments

For information about this vacancy, please contact Prof. Rob Goverde (Digital Rail Traffic Lab), email: R.M.P.Goverde@tudelft.nl, or Dr. Niels van Oort (Smart Public Transport Lab), email: N.vanOort@tudelft.nl.

Web site for additional job details

Offer Requirements

Specific Requirements

You satisfy the following profile.

  • An MSc degree in Operations Research, Transport, or related field.
  • A background in optimization models, transport modelling, or data analytics.
  • A passion for scientific research in close cooperation with practice.
  • Affinity and strong interest in passenger railway transport.
  • Excellent communication skills in English, both written and oral.
  • Knowledge of the European railway context is appreciated.
  • Mastering the Dutch language is an advantage, but not necessary.

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.

Work location(s)
1 position(s) available at
Delft University of Technology
Netherlands
Delft
2628 CD
Mekelweg 2

EURAXESS offer ID: 629748
Posting organisation offer ID: 299652

Disclaimer:

The responsibility for the jobs published on this website, including the job description, lies entirely with the publishing institutions. The application is handled uniquely by the employer, who is also fully responsible for the recruitment and selection processes.

 

Please contact support@euraxess.org if you wish to download all jobs in XML.