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IDEAMAPS PhD Scholarship - Participatory urban analytics for modelling urban deprivation

   College of Social Sciences

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  Prof Joao Porto de Albuquerque  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

Information on the School/Research Group

This PhD scholarship will be hosted at the Urban Big Data Centre (UBDC) & Urban Studies to work on the IDEAMAPS data ecosystem project funded by the Bill & Melinda Gates Foundation.

The Urban Big Data Centre (UBDC) is a research centre and national data service based at the University of Glasgow. We promote the use of big data and innovative research methods to improve social, economic and environmental well-being in cities.

The IDEAMAPS Data Ecosystem project will co-design and develop a participatory data-modelling ecosystem to produce deprived area maps routinely and accurately at scale across cities in lower-middle-income countries (LMIC) to support multiple local stakeholders in their decision-making. It works with stakeholders and a multidisciplinary team to develop methods and digital tools to combine artificial intelligence (AI) analysis of earth observation data with community mapping and engagement to improve how we define and understand areas of deprivation ("including so-called slums") in cities. The project integrates multiple public, official, and community-generated datasets to produce granular surface maps of deprived areas across the pilot cities of Kano and Lagos (Nigeria) and Nairobi (Kenya) in the first phase.


This PhD will develop novel modelling approaches and methods for estimating the locations and types of multiple deprivations across a city. It will work with research partners and stakeholders of the IDEAMAPS Data Ecosystem project to develop a participatory Artificial Intelligence approach (Lee et al. 2019) to urban deprivation modelling workflows, not only with users of our model(s), but also with the residents and local administrators who live and work in the areas being modelled (i.e., data subjects). Model outputs should reflect the needs of model users (e.g., decision-makers), for example, being transferable, scalable, and trusted across diverse settings. Additionally, model outputs will also reflect the perspectives of data subjects, preventing social privileges to be wired into data and models because of unequal opportunities to create, access and use it, as well as ensuring privacy requirements are met to avoid increased surveillance of already marginalised people.

The PhD student will develop interdisciplinary work cutting across urban studies, urban analytics, geographic information science, remote sensing, and participatory/citizen science research. They will be responsible for co-developing and evaluating a modelling workflow for predicting the distribution and characteristics of deprived areas in Lagos by extending previous work on empowering modes of engaging marginalised people (Porto de Albuquerque and Almeida, 2020 ; Elias & Porto de Albuquerque, 2022) and on integrated approaches to modelling deprived areas with participatory modelling processes (Abascal et al. 2021; Thompson et al. 2020). The student will have the opportunity to work closely with supervisors in Glasgow and at the University of Lagos (Nigeria), as well as interact within the multidisciplinary IDEAMAPS team and the stakeholders of governments and community partners.

Candidates should have a master’s degree (or overseas equivalent) with a significant component in working with geographic data, e.g., through courses such as geographic information systems (GIS), remote sensing (RS), software engineering, data science. They can come from a background either in the social sciences (e.g., geography, urban planning, etc.) or in computer/engineering sciences (e.g., computer science, engineering, applied maths, etc.), but with an interest to do interdisciplinary research and develop skills to work in a multidisciplinary team. Candidates should have a demonstratable interest in global urban studies, especially on urban issues in the global south. A foundational understanding of participatory and citizen science methods would be a plus.


Applicants must meet the following eligibility criteria:

*Applicants will have a good Master's degree (or overseas equivalent) with a siginifant component in geographic information systems (GIS) and/or remote sensing (RS) and/or software engineering and/or data science

*Applicants will have a demonstratable interest in the global urban studies, especially in the global south.

*Applicants will have a foundational understanding of particpatory and citizen science methods.

*Applicants can study part-time or full-time.

*Applicants will have a broad social science background.

Please note that all applicants must also meet the entry requirements for the Urban Studies, PhD.

Application process

Applicants must apply via the Scholarships Application Portal, uploading the following documentation:

  • IDEAMAPS PhD Scholarship application form (in Word format)
  • Academic transcripts (All relevant Undergraduate and Master’s level degree transcripts (and translations, if not originally in English) – provisional transcripts are sufficient if you are yet to complete your degree).
  • Academic Prizes
  • 2 written references (where possible your references should include an academic familiar with your work. Both references can be from academics but you may include a work reference, especially if you have been out of academia for more than 5 years).
  • Curriculum Vitae (CV) (academic where applicable).

Funding Notes

Award details
The scholarship is available as a +3 programme only. The programme will commence in October 2023. The funding includes:
* An annual maintenance grant (stipend) at the UKRI rate
* Fees at the standard home or international rate
* Students can also draw on a Research Training Support Grant, usually up to a maximum of £750 per year


Abascal, A., Rothwell, N., Shonowo, A., Thomson, D. R., Elias, P., Elsey, H., Yeboah, G., & Kuffer, M. (2022). “Domains of deprivation framework” for mapping slums, informal settlements, and other deprived areas in LMICs to improve urban planning and policy: A scoping review. Computers, Environment and Urban Systems, 93(February), 101770.
Elias, P., Porto de Albuquerque, J. (2022). Data and the Localization of Sustainable Development Goals in Africa: The Case of SDG 11 in Lagos and Accra. In: Croese, S., Parnell, S. (eds) Localizing the SDGs in African Cities. Sustainable Development Goals Series. Springer, Cham.
Berditchevskaia, A., Malliaraki, E., & Peach, K. (2021). Participatory AI for humanitarian innovation. Nesta, September.
Lee, M. K., Kusbit, D., Kahng, A., Kim, J. T., Yuan, X., Chan, A., See, D., Noothigattu, R., Lee, S., Psomas, A., & Procaccia, A. D. (2019). WebuildAI: Participatory framework for algorithmic governance. Proceedings of the ACM on Human-Computer Interaction, 3(CSCW).
Porto de Albuquerque, J., & Almeida, A. A. de. (2020). Modes of engagement: reframing “sensing” and data generation in citizen science for empowering relationships. In T. Davies & A. Mah (Eds.), Toxic truths (pp. 267–281). Manchester University Press.
Thomson, D. R., Kuffer, M., Boo, G., Hati, B., Grippa, T., Elsey, H., Linard, C., Mahabir, R., Kyobutungi, C., Maviti, J., Mwaniki, D., Ndugwa, R., Makau, J., Sliuzas, R., Cheruiyot, S., Nyambuga, K., Mboga, N., Kimani, N. W., de Albuquerque, J. P., & Kabaria, C. (2020). Need for an Integrated Deprived Area “Slum” Mapping System (IDEAMAPS) in Low- and Middle-Income Countries (LMICs). Social Sciences, 9(5), 80.
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