At a Glance
- Tasks: Conduct innovative research on dependence modelling using advanced statistical techniques.
- Company: Join a leading academic institution with a focus on cutting-edge research.
- Benefits: Gain valuable research experience and access to specialist facilities.
- Other info: Self-funded position with potential for tuition discounts for UEA alumni.
- Why this job: Make a significant impact in fields like finance, health, and environmental sciences.
- Qualifications: 1st class Bachelor's or Master's in Mathematics, Statistics, or Actuarial Science required.
Primary Supervisor: Dr. Aristidis K. Nikoloulopoulos
Multivariate response data abound in many applications including insurance, risk management, finance, psychometrics, health and environmental sciences. Data from these application areas have different dependence structures. While a multivariate distribution fully encodes this dependence, the tractable families used in practice often impose restrictive marginal or dependence structures. Copula functions alleviate these constraints by separating the margins from the dependence structure. Although classical copulas are naturally suited to low-dimensional settings, vine copulas extend the framework to high dimensions. We have shown that a vine copula displays (tail) dependence in all bivariate margins provided that the pair-copulas in the first level possess (tail) dependence; higher-level pair-copulas may be independence copulas without loss of overall (tail) dependence. This insight justifies truncating the vine after the first level, creating a parsimonious model that retains the essential dependence structure. In this project, we will make use of truncated vine copulas with both observed and latent variables in the aforementioned application areas.
Entry Requirements:
- The entry requirements are either a 1st in your Bachelor's degree or a Master's in Mathematics, Statistics, or Actuarial Science.
Mode of study: Full or Part time
Start date: 1st October 2026
Funding: This project is offered on a self-funded basis. It is open to applicants who are self-funded or who are in the process of securing external funding. A bench fee is payable in addition to the tuition fee, to cover the cost of specialist equipment and laboratory facilities required for the research. Applicants should contact the primary supervisor for details of the bench fee applicable to this project. If you are part of the UEA alumni community, you may be eligible for a tuition fee discount. For information on doctoral funding, visit our Postgraduate Student Loans page.
PhD Studentship - Dependence Modelling using Truncated Vine Copulas with Applications (NIKOLOUL[...] in Norwich employer: University of East Anglia
As a leading institution in the field of research and academia, we offer PhD students an exceptional opportunity to engage in cutting-edge projects under the guidance of esteemed supervisors like Dr. Aristidis K. Nikoloulopoulos. Our vibrant work culture fosters collaboration and innovation, while our commitment to professional development ensures that students have access to resources and support for their academic growth. Located at a prestigious university, this role not only provides a platform for meaningful research but also connects you with a diverse community of scholars and professionals dedicated to advancing knowledge in mathematics, statistics, and actuarial science.
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We think this is how you could land PhD Studentship - Dependence Modelling using Truncated Vine Copulas with Applications (NIKOLOUL[...] in Norwich
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Personalise Your Cover Letter:Use your cover letter to show how passionate you are about data science. Describe why you're excited about the opportunity at University of East Anglia and how the role aligns with your career goals in this dynamic field. We want to see your enthusiasm and potential to grow.
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How to prepare for a job interview at University of East Anglia
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Make sure you're ready to chat about the tools we use in data science, like Python, R, or SQL. Brush up on key concepts like data cleaning, analysis, and visualisation — interviewers often delve into these areas to see how you think and approach problems.
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As a trainee, it’s all about showing your enthusiasm for data science! Share any personal projects, online courses, or relevant experiences. This tells University of East Anglia that we’re eager to grow and develop our skills in this exciting field.
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Use this opportunity to find out more about the team’s projects and tools. Questions like ‘What data challenges are you currently facing?’ can demonstrate our interest while also helping us understand how we might fit into University of East Anglia’s culture and workflow.
