Open PhD Position - PHOEBE Project (TSE 121)

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

Safer urban environments are needed for all road users to ensure the European targets to halve road deaths and injuries by 2030 are met. Vulnerable road users require specific attention in an urban environment that is subject to constant change as new forms of transport and micro-mobility enter the system. Existing traffic simulation models allow changes in traffic conditions to be tested but are often vehicle and travel time focused and do not measure detailed outcomes specific to vulnerable road users and road safety. City administrations and transport managers will benefit from predictive tools that allow these changes and their implications for road safety, mobility, and sustainable transport to be anticipated, and support the associated policy, regulatory and consumer response. The Predictive Approaches for Safer Urban Environments project (PHOEBE) will move beyond the state of the art and deliver an interdisciplinary solution that will integrate traffic simulation, road safety assessment, human behaviour, mode shift and induced demand modelling and new and emerging mobility and telematics data into a harmonised, prospective assessment framework for road safety. The PHOEBE framework, software module and knowledge products will allow dynamic safety prediction and socioeconomic evaluation that is evidence-based and simulates future scenarios and impacts.

TSE will lead multiple tasks in this project, such as the socioeconomic analysis methodology, modal shift due to emerging mobilities, the development of methodologies and the assessment of the overall proposed safety measures' impacts on the socioeconomic characteristics.

The successful candidate will be able to contribute to the PHOEBE project, Horizon Europe project, which is an inter-disciplinary project focusing on traffic safety integration with traffic simulation considering vulnerable road users’ groups to develop an enhanced more heuristic road safety assessment framework. The PhD researcher will be supervised by Prof. Dr. Constantinos Antoniou.



  • Having an MSc degree in a relevant field (e.g. transportation engineering, data science, computer science)
  • Be enthusiastic about performing research on transport-related data analytics, and modeling
  • Have a strong background in transportation modelling
  • Have strong analytical skills – e.g. statistics, machine learning, and probability theories 
  • Excellent research, academic writing and presentation skills
  • Like programming, and have an experience of using Python or R
  • Have excellent working knowledge (written and oral) of English, and German
  • Be able to work with strict deadlines
  • Experience with European funded projects will be considered as a plus


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

Conditions of employment

TUM offers a competitive compensation package in accordance to Public Sector Collective Agreement of Länder (TV-L). This position is a 100% TV-L 13 initially funded for three years (A13 a.Z. or E13, depending on the circumstances of the successful applicant). The position expected start date is November 2022. More information on the offered wages can be found at

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

Please include the position ID in the email subject (e.g. [TSE121] and your name).

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