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Bloomsbury Colleges PhD Studentship: AI and Geospatial Accessibility Model Development

Background

Project title: Developing Geospatial Accessibility Models for Healthcare Facilities to Improve Access for People with Disabilities.

In collaboration with the International Centre for Evidence in Disability (ICED) at LSHTM and the Birkbeck Institute for Data Analytics (BIDA), the project will combine expertise in disability research and data science. The application will be validated through user testing with disabled individuals and caregivers, ensuring it reflects real-world accessibility needs. Insights from the project will also contribute to urban planning and healthcare policy by offering data-driven recommendations for improving facility accessibility. The project not only addresses an urgent societal need but also showcases the power of interdisciplinary research to solve real-world challenges.

Project details

  • Project description
    • This project aims to improve healthcare accessibility for people with disabilities by developing a geospatial accessibility model using advanced machine learning techniques. By integrating publicly available big data sources, such as OpenStreetMap (OSM), WheelMap, and patient reviews from platforms like Yelp, the project will analyse facility infrastructure and user feedback to generate accessibility scores for healthcare facilities. 
    • The model will focus on wheelchair users while being adaptable to other disabilities, enabling individuals and caregivers to make informed decisions about suitable healthcare options. Utilising tools like transformer-based masked autoencoders, the project will uncover complex patterns in the data and create a user-friendly web or mobile application to provide accessibility insights.
  • Significance
    • This project has the potential to greatly improve healthcare access for people with disabilities by:
      • empowering individuals and caregivers to make informed decisions about accessible healthcare facilities
      • providing healthcare providers with metrics to enhance their facility’s accessibility
      • contributing to urban planning and healthcare policy by offering large-scale, data-driven insights into facility accessibility
      • paving the way for further applications of ML and geospatial data in solving real-world challenges, potentially inspiring future research and development.

Value and length of funding

  • The PhD study will begin in the academic year 2025/26 (October 2025).
  • The studentship will cover Home PhD tuition fees and a stipend (£21,237 for 2025/26) for up to three years.
  • Applicants from outside the UK may apply for this project. However, they will need to find means to cover the difference between the home tuition fees and the overseas through other sources.

Supervision

Candidate requirements

  • Graduates with a good first degree and/or master's degree in data science, computer science, maths, stats, engineering or other relevant sciences. Applicants with an interest and aptitude for AI in healthcare, as well as for geospatial data analysis and quantitative methods are encouraged to apply. Knowledge, understanding or interest in healthcare accessibility development would also be an advantage. 
  • You should be comfortable with managing large files within a programming environment, and with using Python language. The project will require advanced statistical and computational analysis skills (e.g. experience in machine learning and big data analytics).

How to apply

  • Please follow the online application process for the full-time Computer Science PhD at Birkbeck , clearly stating your interest in the ‘Bloomsbury PhD Studentship’ with Dr Paul Yoo.
  • Please use the supporting statement in the application to outline why you are applying for this project, and why you are a suitable candidate for it. 
  • Queries about the PhD and training should be sent to . 

Deadlines and interviews

  • Application deadline: 2 March 2025
  • Interview date: March 2025
  • If you have questions regarding the application process, please contact (PhD Admission Tutor)

More information

  • Further details about the project may be obtained from Dr Paul Yoo (Principle Supervisor) at Birkbeck and Professor Hannah Kuper (Co-Supervisor) at LSHTM. 
  • Find out more about PhDs at Birkbeck.