Coventry University Featured PhD Programmes
Norwich Research Park Featured PhD Programmes
Engineering and Physical Sciences Research Council Featured PhD Programmes
Norwich Research Park Featured PhD Programmes
University of Reading Featured PhD Programmes

PhD studentship in Socio-economic complex systems

This project is no longer listed on and may not be available.

Click here to search for PhD studentship opportunities
  • Full or part time
    Dr V Restocchi
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

One fully funded PhD position to work with Dr. Valerio Restocchi in the School of Informatics at the University of Edinburgh, on a project titled “Socio-economic complex systems”.

The aim of this project is to gain a better understanding of the social dynamics that shape our society. Research in this area has been exponentially growing in the past years, especially thanks to cross-contamination among different disciplines (physics, psychology, economics, mathematics, etc.) and the availability of computational techniques that allow to study large complex systems and analyse even larger amounts of data. Specifically, the candidate will be expected to develop mathematical models of human behaviour, perform social network analyses, and run agent-based or numerical simulations to examine interactions in our society, with primary focus on social influence (e.g., opinions, behaviours, ideas, etc.) propagation across the population.

Possible applications include, but are not limited to:

• Opinion dynamics for politics, economics, and finance
• Propagation of non-contagious diseases such as smoking, alcohol and drug abuse.
• Social dynamics of success (e.g., entrepreneurship, academic, and artistic success)
• Development of targeting strategies (e.g., for crime prevention, digital marketing, policy making)

Candidate’s profile

• A good Bachelors degree (2.1 or equivalent) in a relevant subject (physics, mathematics, engineering, computer science, or related subject)
• Strong programming skills in object-oriented languages (preferably Python)
• Proficiency in English (both oral and written)
• Knowledge of one or more among differential equations and PDEs, statistical physics, parallel computing, and numerical methods is highly desirable.
• Keen and demonstrable interest in at least one of the possible topics (e.g., social systems, health, finance, etc.) is also desirable.

Application Information

Applicants should apply via the University’s adminissions portal (EUCLID) and apply for the following programme: PhD Informatics: CISA: Automated Reasoning, Agents, Data Intensive Research, Knowledge Management - 3 Years (Full-time) with a start date of 01 September 2019.

Applicants should state “PhD studentship in Socio-economic complex systems” and the research supervisor (Dr. Valerio Restocchi) in their application and Research Proposal document.

Applications should be submitted by 1st August 2019. The anticipated start date is 01 September 2019 but an earlier start date can be considered.

Only complete applications will progress forward to the academic selection stage.

Applicants must submit:

• Degree transcripts and certificates (for both BSc and MSc if applicable)
• Evidence of English Language capability (where applicable).
• A short research proposal (max 1 page)
• A full CV and cover letter describing your background, suitability for the PhD, and research interests (max 1 page).
• Two references (note that it the applicant’s responsibility to ensure reference letters are received before the deadline).

Funding Notes

The studentship covers:

• Full time PhD tuition fees for a student with UK/EU nationality (£4,327 per annum, subject to annual increment).
• A tax free stipend of GBP £15,0009 per year for 3 years.
• Additional programme costs of £1000 per year.

Related Subjects

How good is research at University of Edinburgh in Computer Science and Informatics?

FTE Category A staff submitted: 94.85

Research output data provided by the Research Excellence Framework (REF)

Click here to see the results for all UK universities

FindAPhD. Copyright 2005-2019
All rights reserved.