Fully funded PhD Computer Science & AI United Kingdom

PhD Scholarship in Human Navigation, Artificial Intelligence and Neuroscience for Human-Centric Urban Mobility

Technical University of Denmark, United Kingdom

Institution
Technical University of Denmark
Country
United Kingdom
Position type
PhD
Subject area
Computer Science & AI
Location
London, England, United Kingdom
Funding
Fully funded position

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About this position

DTU Management invites applications for a 3-year PhD Scholarship associated with the project “Brains in Motion: Explaining How Humans Learn and Adapt to Navigate Urban Environments Using Artificial Intelligence and Neuroscience.”

The PhD project will be carried out at the Department of Technology, Management and Economics (DTU Management) at the Technical University of Denmark (DTU), in close collaboration with Imperial College London and the new DTU Smart Sensing Lab. The project is supervised by Associate Professor Rico Krueger and co-supervised by Associate Professor Carlos L. Azevedo at DTU, with Professor Aldo Faisal from Imperial College London involved as international project partner.

Research objectives and tasks
You will contribute to the development and empirical validation of models that explain how humans learn, adapt and stabilise navigation behaviour in urban environments. The project will combine methods from transportation science, artificial intelligence, computational neuroscience and behavioural experimentation. 

Key research tasks include:

  • Developing learning-based behavioural models of navigation, route choice and adaptation;
  • Applying reinforcement learning, probabilistic modelling and computational neuroscience to human mobility behaviour;
  • Modelling how people build and update internal representations of urban space;
  • Integrating behavioural data with neurophysiological markers such as eye movements, cognitive load, attention dynamics and eeg-based measures;
  • Designing and conducting immersive virtual reality experiments and naturalistic field studies;
  • Studying behavioural adaptation to changes such as route closures, infrastructure modifications and new mobility technologies;
  • Translating model insights into tools and knowledge relevant for urban planning and transport system design.

The project will have a strong empirical component. The PhD student will work with behavioural data, immersive experimental environments, and human-centric sensing technologies such as eye-tracking, wearables and EEG.

International collaboration

The PhD project is part of a new strategic collaboration between DTU and Imperial College London. You will undertake a 6-month research stay at Professor Aldo Faisal’s Brain & Behaviour Lab at Imperial College London. During the stay, you will acquire technical and methodological expertise in measuring and analysing neurophysiological processes using state-of-the-art sensing equipment. The collaboration will also include joint supervision, regular project meetings, co-authored scientific publications and interaction with a complementary PhD project at Imperial College London.

Qualifications

We are looking for a highly motivated candidate with a strong interest in human behaviour, urban mobility, artificial intelligence and/or neuroscience.

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. Your degree should be in a relevant field, such as:

  • Cognitive Science, Computational Neuroscience, Computational Psychology or Behavioural Science;
  • Transport Modelling, Transportation Science or Urban Mobility;
  • Data Science, Artificial Intelligence, Machine Learning or Computer Science;
  • Human-computer Interaction, Spatial Cognition or related areas;
  • Engineering, Applied Mathematics, Statistics or another Quantitatively Oriented Discipline.

Application procedure 

Your complete online application must be submitted no later than 15 September 2026 (23:59 Danish time)

To view the full announcement and to apply, click the 'Apply' button

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