PhD student in Digital Sensing and Modelling of Travel Behavior and Mental Health

Monday 22 Feb 21

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Apply no later than 15 April 2021
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DTU Management’s Transport Division would like to invite applications for a 3-year PhD position starting no later than June 1st, 2021. The successful candidate will join the Machine Learning for Smart Mobility Group and will work under the supervision of Associate Professor Carlos Azevedo and Senior Researcher Sonja Haustein in collaboration with the Faculty of Medicine of the University of Lisbon.

This PhD project is part of a larger project entitled “eMOTIONAL Cities - Mapping the cities through the senses of those who make them”, funded by the EU Commission’s H2020 Framework and part of the European Cluster on Urban Health.

Project Background
The eMOTIONAL Cities project was designed to provide robust scientific evidence on how the natural and built urban environment shapes the neural system underlying human cognitive and emotional processing. Furthermore, it has the goal to map such neurobiological reactivity through time and space as the urban landscape change. Grasping the spatial cognition of the citizens’ behaviour and decisions while interacting with their real-life surroundings will be a breakthrough, as it will foster more inclusive urban design resulting in better individual health and well-being.

This specific PhD project will focus on the joint sensing and modelling of travel decision, neuro- and bio-signals and mental health, in outdoor environments, with different groups of people and across various urban scenarios.

Together with our team (with a background in discrete choice modelling, psychology, machine learning and technology management) the successful candidate will design, pilot and implement the data collection architecture for outdoor natural experiments, combining existing smartphone- and biosensing-based technologies targeting the exploration of causal relationships between multiple urban environments and individual behavioural signals. Participants will be asked to carry smartphones with apps specifically designed for customized adaptive stated perception surveys regarding context-specific built and travel environment, as well as for detailed data on daily travel and activity patterns across multiple days. Moreover, participants will also wear several types of environmental (for measuring climate and outdoor comfort data) and neurobiological (e.g.: eye tracking glasses, wearable EEG, physiological biosignals) sensors.

Behaviour modelling methods from discrete choice, cognitive processes and machine learning will be used to construct the linkage between context and environmental stimulus, neurophysiological metrics, stated and measured emotional and cognitive indicators and the underlying travel and activity participation decision making.

Finally, the modelled relationships will be integrated in a new activity-based travel behaviour model for scenario evaluation at the urban scale.

Overall, this research lies in the intersection between Behavioural Modelling and Digital Sensing. This is a unique opportunity to build your research profile under a collaborative large network sustained by a European-funded project.

We are looking for excellent applicants with MSc background on Behavioural Modelling, Cognitive Neuroscience, Mental Health, Transportation, Computer Science, Applied Statistics or related.

Responsibilities and tasks

  • Design, implement and pilot the data collection architecture for outdoor natural experiments
  • Develop mathematical models of individual behaviour through the mapping of the underlying neuro- and cognitive- processes and its relationship with mental health
  • Collaborate with researchers from behavioural modelling, computational and neurosciences in a truly interdisciplinary environment.
  • Co-author scientific papers aimed at high-impact journals.
  • Participate in international conferences.
  • Participate advanced classes to improve academic skills
  • Carry out work in the area of dissemination and teaching as part of the overall PhD education.


  • A MSc degree in Behavioural Modelling, Cognitive Neuroscience, Mental Health, Transportation, Computer Science, Applied Statistics or related.
  • Excellent background in statistics and probability theory is required.
  • Good programming capabilities in at least one scientific language is required.
  • Experience with digital sensing is favoured.
  • Behavioural modelling or mental health disciplines in the education background is favoured.

The following soft skills are also important:

  • Curiosity and interest about current and future mobility challenges and digital technologies.
  • Good communication skills in English, both written and orally.
  • Experience in writing and publishing scientific papers is an advantage.
  • Willingness to engage in group-work with a multi-national team.

Approval and Enrolment
The scholarship for the PhD degree is subject to academic approval, and the candidate 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 the DTU PhD Guide

The assessment of the applicants will be made until the position is filled and no later than May 1st 2021. 

We offer
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

Salary and terms of employment
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 3 years.

You can read more about
career paths at DTU here

Further information
For more information, please contact Carlos Lima Azevedo or Sonja Haustein

You can read more about the Machine Learning for Smart Mobility group at and DTU Management at

If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark

Please submit your online application no later than 15 April 2020 (Danish time). Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply online", fill out the online application form, and attach all your materials in English in one PDF file. The file must include:

  • A letter motivating the application (cover letter)
  • Curriculum vitae
  • Grade transcripts and BSc/MSc diploma
  • Excel sheet with translation of grades to the Danish grading system (see guidelines and Excel spreadsheet here)

You may apply prior to ob­tai­ning your master's degree but cannot begin before having received it.

All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply.

The Machine Learning for Smart Mobility group belongs to the Transport division of the Department of Technology, Management and Economics (DTU Management) at DTU. The division conducts research and teaching in the field of traffic and transport behaviour and planning, with particular focus on behaviour modelling, machine learning and simulation.

DTU Management
DTU Management conducts high-level research and teaching with a focus on sustainability, transport, innovation and management science. Our goal is to create knowledge on the societal aspects of technology - including the interaction between technology and sustainability, business growth, infrastructure and prosperity. Therefore, we explore and create value in the areas of management science, innovation and design thinking, business analytics, systems and risk analyses, human behaviour, regulation and policy analysis. The department offers teaching from introductory to advanced courses/projects at BSc, MSc and PhD level. The Department has a staff of app. 350. Read more here.

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