Scale-freeness and growth stability of realistic network models
Interested in studying how network grow? This PhD project will investigate the properties of a stochastic model that generates networks from a probabilistic point of view.
The Barabási-Albert model is a famous model with two seemingly ubiquitous properties: it uses a preferential attachment mechanism, and it generates scale-free networks. According to recent works (Broido and Clauset, 2019; Voitalov et al., 2019), however, real-life networks present a more nuanced picture of scale-freeness. In addition, while the study of scale-freeness focuses on the largest degrees of the network, methods from extreme value theory have been underused. This presents an opportunity to quantify the scale-freeness through a more realistic model.
The aim of this PhD position is to
- Modify or extend the Barabási-Albert model to more accurately describe how real-life networks grow
- Quantify the scale-freeness through a numerical measure e.g. the tail index in extreme value theory
- Study the theoretical properties of such scale-freeness and the large degrees under the modified model when the network keeps growing
Number Of Awards
18th September, 2023
School of Mathematics, Statistics and Physics, Newcastle University
Dr Clement Lee
You must have, or expect to gain, a minimum 2:1 Honours degree or international equivalent in a relevant subject such as Statistics, Mathematics, or another strongly quantitative discipline. Enthusiasm for research, the ability to think and work independently, excellent analytical skills and strong verbal and written communication skills are also essential requirements.
Home and international applicants (inc. EU) are welcome to apply. In the first instance the studentship covers only home tuition fees. The School of Mathematics, Statistics and Physics has very limited additional funding to offer full studentships including international fees to exceptional international applicants.
Applicants whose first language is not English require an IELTS score of 6.5 overall with a minimum of 5.5 in each subsection.
International applicants may require an ATAS (Academic Technology Approval Scheme) clearance certificate prior to obtaining their visa and to study on this programme.
How To Apply
You must apply through the University’s Apply to Newcastle Portal
Once registered select ‘Create a Postgraduate Application’.
Use ‘Course Search’ to identify your programme of study:
- Search for the ‘Course Title’ using the programme code: 8080F
- Research Area: Statistics
- Select ‘PhD Mathematics (full time) - Statistics' as the programme of study
You will then need to provide the following information in the ‘Further Questions’ section:
- A ‘Personal Statement’ (this is a mandatory field) - upload a document or write a statement directly in to the application form
- The studentship code MSP060 in the ‘Studentship/Partnership Reference’ field
- When prompted regarding your research proposal - select ‘Write Proposal’. You should then type in the title of the research project from this advert. You do not need to upload a research proposal.
Contact the supervisor for project specific information. Contact email@example.com for general information on applications.