麻豆果冻传媒

You will be part of a small group of mathematics and statistics PhD students, but part of a wider school and university base that includes, for example, staff and student researchers in computing and engineering, facilitating further potential for interdisciplinary interactions. To help you build your academic network, you will be aligned with the Computing and Mathematical Science Research Excellence Group. Other groups and centres at the university are also open to PGR members from the maths department. 

This drives and informs the research through a wide range of topics based around three research areas:

• Computational methods
• Discrete mathematics
• Statistics and operational mathematics. 

We also welcome mathematics and statistics PhD students whose original research is developed through interdisciplinary projects, offering a wealth of close interaction with the university's science departments. We have had many successful PhDs that connect with areas such as biology (eg big data analysis) and computing (eg visualisation) or financial mathematics. 

We have a strong reputation in a range of topics in mathematics, which is strengthened by collaborations with many UK and international academic institutes (eg University of Liverpool; Durham University; Royal Holloway, UK; University of Rome, Italy; University of Montepellier, France) and industrial partners (for example, Hurstwood Park Neurosciences Centre, Haywards Heath, UK;  Southern Water, UK; and Poste Italiane, Napoli, Italy).

The focus of mathematics research at the University of 麻豆果冻传媒 is into the use of applied numerical methods, with close relationships with research progressing biomedical sciences, computing and engineering.

We would be particularly interested in projects that aligned to one or more of these long-standing strengths at the university: 

• Computational methods focuses on the development of numerical methods for solving problems in applied mathematics and engineering. Avenues of interest include finite element methods, boundary element methods and the machinery which underpins these, such as numerical methods of linear algebra. These methods have been applied to problems as diverse as modelling the sound field radiated from a loudspeaker to modelling the formation and growth of cavities in the spinal cord.
• Discrete mathematics is interested in the development and application of discrete mathematical techniques, particularly as applied within computer science. Areas of interest include logic, formal languages, algebraic structures, algorithms, graph theory, combinatorial and computational geometry and topology. These methods have been applied to the development of visual logics to assist human reasoning, the development of information visualisation algorithms which automatically generate diagrams, and efficient knot detection with biological applications.
• Statistics and operational research has a wide range of research interests from theoretical probability to applied statistics and rigorous machine learning. Examples of current work are the application of financial and operational research methods for pricing financial and energy instruments and analysing investment incentives, the development of statistical methodologies for analysing big data studies, the development of marginal regression models with correlated discrete response variables, the theoretical analysis of online prediction models and the application of topological data analysis methods.

Research supervisors for your PhD research programme

As a mathematics postgraduate you will benefit from research supervision comprising two or maximum three members of academic staff. Depending on your research specialism one of those supervisors may be from another school, another research institution, or could include an external partner. 

You will identify your potential mathematics research supervisor from the early stages of application and they will usually then support you throughout your programme of study, helping you carry out your research interests, guiding your learning of rigorous research methods and preparing you for the next stage of your career.

You should consider the staff listed below and create a short draft research proposal identifying your suitability for supervision from that person's research specialism. If you discuss your research with a potential supervisor it is likely to improve your opportunity to study with us. 

Research training and support

The independent research programme for mathematical research is balanced and enhanced with a range of support from your supervisors and the extended academic community. You and your fellow postgraduate research students will have the opportunity to attend and present at research seminar sessions at the Computing and Mathematical Science Research Excellence Group with guests from professional and academic spheres. The PhD programme will give you the opportunity to build research skills as well as developing transferable skills essential for employment and practice within mathematics and its related fields.

As a member of the 麻豆果冻传媒 Doctoral College, you will benefit from regular opportunities on a training programme designed to support postgraduate researchers at all stages of the PhD and help them achieve their career goals. Attendance at appropriate workshops within this programme is encouraged, as is involvement with the annual Festival of Postgraduate Research. Academic and technical staff also provide more subject-specific training. 

You will benefit from access to all necessary research resources, including a contemporary range of electronic resources via the university’s Online Library, as well as the physical book and journal collections housed within campus libraries. The library services are connected to national and international collections and students also have the option of inter-library loans.

We strongly recommend that you apply with the support of one of our academics. By establishing your supervisor from the early stages of application, you will be supported through the application process and can make the best start to your programme of study.

You should consider the staff listed below and create a short draft research proposal identifying your suitability for supervision from that person's research specialism and your place in the wider context of the department's research ambitions. Their contact details are available on their full profile.

Our primary staff supervising in the discipline are listed. For further information on university supervisory staff, including cross-disciplinary options, please visit 

I am interested in supervising postgraduate research projects related to mathematically intensive methods of machine learning. My main area is sequential online forecasting, particularly prediction with expert advice. I am also interested in reinforcement learning (especially as a generalisation of online forecasting), kernel methods and topological data analysis.

I supervise PhD students who use numerical methods (such the boundary element method and finite element method) to solve problems in applied mathematics.

PhD projects that I am interested in supervising include using combined boundary element and finite element methods for modelling the motion of biological cells due to chemotaxis, the use of the finite element method to model deformations of the spinal cord (in relation to the medical condition syringomyelia) and the use of the finite element method in image analysis (such denoising images and segmenting images).

Supervision Opportunities in Bibliometrics & Scientometrics

I welcome PhD, Master's, and undergraduate students interested in exploring the dynamic landscape of scholarly communication, research evaluation, and science policy through the lens of bibliometrics and scientometrics. My supervision integrates data analytics, machine learning, and open science principles to address pressing questions in global research ecosystems.

Some research ideas:

• Science & Economy Nexus

  • Investigate how economic indicators influence scientific output across countries, institutions, and disciplines.

• Citation Dynamics

  • Citation flows between collaborating nations or institutions. Citation networks and their evolution over time.

• Global Research Collaborations

  • Study patterns of collaboration at institutional, national, and international levels. Examine the role of geopolitical factors in shaping research partnerships.

• Sustainable Development Goals (SDGs)

  • Quantify research contributions to specific SDGs. Conduct gender-based analyses of SDG-related publications.

• Cybersecurity in Scientometrics

  • Explore bibliometric approaches to understanding cybersecurity research trends. Assess the resilience of research infrastructures to cyber threats.

• Horizon Scanning & Emerging Topics

  • Create predictive models to identify emerging areas of research and detect changes in scientific discourse.

• Mobility & Collaboration

  • Analyse the connection between international mobility and collaborative outputs. Use author affiliation data to track research migration patterns.

• Open Science & Integrity

  • Assess the citation benefits of open-access publications. Examine the proliferation and influence of predatory publishing.

• Institutional Research Profiles

  • Profile higher education institutions based on publication and citation metrics. Assess institutional strategies for enhancing scientific productivity.

• Mapping Science

  • Create visualisations of disciplinary landscapes and national research portfolios to uncover hidden structures in science.

Current PhD Supervision

Lead PhD supervisor for Minsoo Kim - Developing a citation prediction model.

I am interested in supervising postgraduate research students in machine learning methods, categorical data analysis, multivariate analysis and high-dimensional statistics. Projects are likely to involve development of open-source software to support and disseminate the findings of the research.聽聽