Portrait photo of Philip Leifeld (c) John Cooper

Philip Leifeld


Accepting PhD Students

PhD projects

Professor Leifeld is interested in supervising well-trained and ambitious PhD researchers. Topics should be related to political networks, complex social systems, or research methods. Candidates should be willing to apply for funding or come with existing PhD funding. Prior undergraduate or postgraduate training in the social sciences (e.g., politics, economics, sociology) or a STEM discipline (e.g., statistics, computer science) is required. Professor Leifeld is particularly interested in PhD supervision in the areas of policy networks, discourse networks, UK higher education policy, environmental or social policy, and the development and application of network science, Bayesian inference, or likelihood-based statistical inference with a view to questions in the political or social sciences.

Personal profile


Philip Leifeld is a professor in social statistics. His main research interests are politics and public policy, network analysis and complex systems, statistical inference, and computational social sciences.

Office hours

Tuesdays 10am-12pm during term time, room G29 in the Humanities Bridgeford Street building.

Further information

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being
  • SDG 12 - Responsible Consumption and Production
  • SDG 13 - Climate Action

Areas of expertise

  • H Social Sciences (General)
  • HA Statistics
  • JA Political science (General)
  • JF Political institutions (General)


  • Network analysis
  • Networks
  • Complex systems
  • Politics
  • Policy
  • Institutions
  • Policy research
  • Governance
  • Political communication
  • Research design
  • Research methods
  • Programming
  • R
  • Java
  • C++
  • Statistics
  • Computational statistics
  • Statistical inference


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