PhD Positions (2) in Advanced Methods for Human Behaviour Analysis in Future Transport Systems Using Virtual Reality – DTU Management

The Division for Transportation Science at the Technical University of Denmark (DTU) invites applications for two PhD positions in Advanced Methods for Human Behaviour Analysis in Future Transport Systems Using Virtual Reality. The positions focus on developing and testing the next generation of mathematical models for explaining and predicting human behaviour and decision-making in the context of future transport and infrastructure systems using data collected through immersive virtual reality experiments. 

The PhD positions are part of the research project IMMERSION: Explaining human decision-making by combining choice and process data, which is funded by a European Research Council (ERC) Starting Grant. IMMERSION aims to advance the study of human decision-making by developing new innovative methods for combining choice and neurophysiological process data. This entails new models for integrating choice and process data, new statistical inference procedures tailored to such models, and new methods for collecting rich behavioural data in immersive experiments. The project also includes substantial empirical work applying IMMERSION’s methodological innovations to real-world problems with implications for the human-centric design of future transport systems. This includes case studies to explain and predict human decision-making in the contexts of transportation infrastructure development, pedestrian-autonomous vehicle interactions and pedestrian wayfinding.

You will join a diverse research team led by Associate Professor Rico Krueger, and you will be a member of the Intelligent Transportation Systems (ITS) section within the Division for Transportation Science at the Department of Technology, Management and Economics (DTU Management) at DTU. You will be supervised by Associate Professor Rico Krueger and Professor Francisco Pereira.

Responsibilities and qualifications
The two PhD positions are associated with distinct subprojects:

• In subproject 1, you will work on developing new flexible modelling and fast estimation approaches for combining choice and process data using probabilistic machine learning methods.
• In subproject 2, you will work on creating new modelling and estimation approaches to strategically and effectively integrate choice data with diverse types of process data. This will involve leveraging explainable machine learning and information fusion methods. 

In both subprojects, you will:

• Formulate and test new modelling approaches at the interface of machine learning, cognitive psychology, economics and statistics for explaining and predicting human behaviour and decision-making using both choice data and neurophysiological process data,
• Devise and evaluate new estimators for parameter inference in the proposed models using advanced statistical and computational approaches, including Bayesian methods and other simulation-assisted methods,
• Design, implement and conduct immersive virtual reality experiments to study human behaviour and decision-making in the context of future transport and infrastructure systems,
• Support data collection efforts involving the use of immersive virtual reality technologies and neurophysiological sensors (e.g. to gather biomarker, neuroimaging and eye-tracking data),
• Write academic papers aimed at high-impact journals,
• Participate in international conferences and workshops,
• Collaborate with other team members and our international research partners.    

You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree. Specifically, we seek applicants with a master's degree in transport, mathematics, statistics, computer science, economics, psychology, human factors, civil engineering, industrial engineering or a related discipline.

You should have experience in some, but not necessarily all, of the following areas: mathematical modelling, statistics, machine learning, artificial intelligence, design and implementation of virtual reality experiments, data collection and analysis. Proficient English language skills as well as programming skills in Python, Julia, R or similar are also required. 

Approval and Enrolment 
The scholarships for the PhD degree are subject to academic approval, and the candidates will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education.

Assessment
The review of applications will begin on 16 February 2025.

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