Open PhD Position - MO3 Project (TSE107)

Chair of Transportation Systems Engineering (TSE)

The chair of Transportation Systems Engineering focuses on performing transportation research surrounding aspects of modelling and simulation of transportation systems, implementation of data science and data analytics in transport and human factors analysis. Specifically, the TSE chair performs research on both multimodal and unimodal freight and passenger transport demand and supply modelling, allowing for contributions on optimisation, calibration and validation of transport models. In this direction, the application of Big Data acquisition and analysis is examined as well as the use of Data-driven flexible models. Finally, the TSE chair contributes on the analysis of human factors analysis in transport-related fields such as road safety modelling, behavioural economics applications and modelling of factors that affect transportation systems user engagement.

Position Description

The position is funded by International Graduate School of Science and Engineering - IGSSE. The successful candidate will explore the extent to which mobility patterns derived by diverse data sources can be used (as RP data) to support the development of discrete choice route choice and mode choice models, in response to changing conditions. The scarcity and cost of collection of RP data has arguably always been the biggest limiting factor for the development of powerful discrete choice models, reflecting actual mobility decisions. The advances of sensing and communications technologies have provided alternative, more effective ways to obtain direct observations; however, these are still limited by various technical and non-technical (e.g. privacy) restrictions. In this thesis, we will explore the use of emerging data collection techniques, within the framework of RP observations, and combine them with other information (e.g. obtaining information about the attributes of non-chosen alternatives from services, such as Google Maps APIs) to develop rich, large-scale databases for the support of the estimation of a new generation of mobility models. An application of these models could be response to anomalies in metro networks, and the ability to sense, in real-time, the demand patterns, in order to effectively operationally respond with measures, such as bus-bridging the affected portions of the network.

Information on the project can be found here

Information on the funding organisation can be found here


Candidates are required to:

  • hold a Master of Science diploma in a relevant field of study
  • be enthusiastic about performing research on transportation modelling
  • have strong analytical skills – e.g. statistics, machine learning, optimization
  • be an analytical mind
  • like programming
  • have excellent working knowledge (written and oral) of English
  • be able to work with strict deadlines

Additionally to the above, candidates must fulfil the TUM admission requirements 

Conditions of employment

TUM offers a competitive compensation package for PhD students. This position is funded by a stipend of 2000 euros per month, that is increased based on the family status. 

The position is immediately available. 

TUM is an equal opportunity employer. Qualified women are particularly encouraged to apply. Applicants with disabilities are treated with preference given comparable qualification.



Interested applicants who fit the requirements of the position are asked to send the following to

  • a CV
  • academic transcripts
  • a motivation letter
  • the names and contact information of three references

Review of applications will begin immediately and continue until the position is filled.