PhD Studentship: Tackling Societal Challenges With Complex Systems and Computational Social Science. PhD in Computer Science Ref: 5070

The University of Exeter’s College of Engineering, Mathematics and Physical Sciences  is inviting applications for a fully-funded PhD studentship to commence as soon as possible. The studentship will cover Home tuition fees plus an annual tax-free stipend of at least £18,622 for 3.5 years full-time, or pro rata for part-time study.

This studentship is open to UK and international applicants.

Project Description:

In this project, you will investigate the complexities of societal challenges using advanced (explicit) computational models. Your research will focus on applying and developing sophisticated modelling techniques to explore the interplay of socioeconomic factors on social phenomena.

Instead of black-box models, you will delve into the realm of complex adaptive systems, investigating how individual and collective behaviours emerge and influence societal outcomes over time. The project aims to characterize and uncover social mechanisms by modelling, simulating, analysing, and predicting social trends and regularities.

This project takes shape around your expertise and background. Depending on your background, you will focus on either of the following distinct areas: (1) the mechanisms of crime in cities, (2) understanding inequality via generative network models, and (3) network effects on how beliefs and attitudes spread.

In this project, you will use (learn) approaches based on network science, machine learning, information theory, agent-based and mathematical modelling, mean-field theory, among others.

This project is intrinsically interdisciplinary, and you must enjoy and challenge diverse ideas collaboratively.

References:

• Epstein, J. M. (2008). Why model? Journal of artificial societies and social simulation, 11 (4), 12.
• D'Orsogna, M. R., & Perc, M. (2015). Statistical physics of crime: A review. Physics of Life Reviews, 12, 1-21.
• Oliveira, M. et al. (2022). Group mixing drives inequality in face-to-face gatherings. Communications Physics, 5(1), 127.
• Oliveira, M., et al. (2017). The scaling of crime concentration in cities. PloS one, 12(8), e0183110.
• Miller, J. H., & Page, S. E. (2009). Complex adaptive systems: an introduction to computational models of social life. Princeton University Press.
• Epstein, J. M. (2012). Generative social science: Studies in agent-based computational modeling. Princeton University Press.

For more information, please do not hesitate to contact: Dr. Marcos Oliveira m.a.oliveira@exeter.ac.ukhttps://marcosoliveira.info/

Entry requirements

This studentship is open to UK and International applicants.

Applicants should have, or expect to achieve, at least a 2:1 honours degree (or equivalent international qualifications) in Computer Science, Physics, Mathematics, Statistics, Economics, or a related subject, or the equivalent qualifications gained outside the UK. A relevant Master's degree and/or experience in computational or mathematical modelling would be an advantage.

If English is not your first language you will need to have achieved at least 6.0 in IELTS and no less than 6.0 in any section by the start of the project.

Alternative tests may be acceptable (see http://www.exeter.ac.uk/postgraduate/apply/english/).

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