Why study this course?
There is a growing worldwide demand for students with skills in mathematical biology academic research, as well as in the life sciences industrial sector, including biotechnology, biomedical, healthcare and pharmaceutical companies.
- Take a course of study tailored to your interests
- Explore modern and relevant ideas in mathematical biology
- Be ready to pursue a PhD and academic career in mathematical biology
- Acquire the qualifications and skills for a career in the biomedical sector
Teaching
A mix of lectures, small group tutorials and practical computer sessions.
Class sizes
From 10 to 60 students.
Dissertation
An end-of-course project with ongoing support.
Assessment
A mix of continuous assessment and exams.
Modules
The St Andrews degree structure is designed to be flexible. You study compulsory modules delivering core learning together with optional modules you choose from the list available that year.
If you choose not to complete the dissertation requirement for the MSc, there is an exit award available that allows suitably qualified candidates to receive a Postgraduate Diploma (PGDip) instead, finishing the course at the end of the second semester of study.
For more details, including weekly contact hours, teaching methods and assessment, please see the module catalogue. The modules are examples from previous academic years and may be subject to change before you start your course.
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- Spatial Models and Pattern Formation in Mathematical Biology: explores applications of partial differential equation to real world biological and medical problems, e.g., cell migration, pattern formation in animal coat markings, spread of infectious diseases, and more.
- Stochastic Dynamics in Biology: provides an introduction to stochastic mathematical modelling with a focus on applications in biology, such as gene regulation, and the dynamics of cell- or animal populations.
- Mathematical Oncology: using a wide range of methods and techniques we develop and study mathematical models addressing biomedical questions in cancer growth, metastasis and treatment.
- Advanced Computational Techniques: studies several ideas and techniques that underpin modern numerical treatment of processes described by partial differential equations.
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Students choose two optional modules from this list:
- Applied Statistical Modelling using GLMs: covers the main aspects of linear models and generalised linear models, including model specification, various options for model selection, model assessment and tools for diagnosing model faults.
- Calculus of Variations in Biological Modelling: using variational techniques as a main tool, we develop mathematical models for various biological phenomena including cell migration, protein structure, and limb regeneration.
- Computational Numerical Analysis: introduces programming for the implementation of mathematical algorithms to solve a wide range of mathematical problems.
- Introductory Data Analysis: covers essential statistical concepts and analysis methods relevant for commercial analysis.
- Modelling Wildlife Population Dynamics: introduces students to methods for constructing mathematical models of wildlife population dynamics and of fitting these models to diverse data from wildlife surveys.
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Students choose one optional module from this list:
- Advanced Analytical Techniques: introduces important advanced applied analytic techniques such as variational calculus, integral equations, solutions to differential equations by contour integrals, and the theory of steepest descent.
- Estimating Animal Abundance and Biodiversity: introduces the main types of survey methods for wildlife populations.
- Fluid Dynamics: introduces the theory of incompressible fluid dynamics, with particular attention to conservation laws.
- Medical Statistics: covers a number of key topics in the field that are important for both methodological development and application.
- Population Dynamics Models in Mathematical Biology: explores applications of difference and ordinary differential equations mathematics to real world biological problems e.g., harvesting of fish stocks, host-parasitoid systems, predator-prey dynamics, and more.
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MSc students complete a dissertation during the final three months of the course to be submitted near the end of August. Dissertations are supervised by members of teaching staff who will advise on the choice of subject and provide guidance throughout the progress of the dissertation.
What it will lead to
Careers
The skills obtained during this MSc programme are highly valued for a PhD and further academic career in mathematical biology as well as for a professional research scientist career in the private sector.
These skills are sought after, among others, in advanced Research and Development positions in:
- pharmaceutical companies
- medical devices companies
- life-sciences industry
We are committed to supporting your career aspirations, whatever stage your career is at.
Our Careers Centre can help connect you to our extensive global alumni community for advice and mentoring, as well as offering career coaching, bespoke workshops, employer connections, experiences, and application support.
Our International Education and Lifelong Learning Institute can also support you with academic and professional skills development.
Elevate your career
Graduates from Mathematics and Statistics MSc programmes have gone on to work in a variety of organisations, including:
- Civil Service
- DEFRA
- King's College London
- World Bank
Further your education
Many graduates of the MSc programmes in the School of Mathematics and Statistics continue their education by enrolling in PhD programmes at St Andrews or elsewhere.
Go your own way
Our Entrepreneurship Centre offers training and start-up support, gives you access to experienced and expert mentors and an investor network, and one-to-one advice to help you realise your commercial potential.
Why St Andrews?
The School of Mathematics and Statistics has active research groups in:
- Applied Mathematics
- Mathematical Biology
- Pure Mathematics
- Statistics
Events
There are a number of different seminars held each week in the School of Mathematics and Statistics. These include:
Statistics
- Centre for Research into Ecological and Environmental Modelling seminars
- Statistics seminars
- National Centre for Statistical Ecology seminar series
Pure Mathematics
- Pure Mathematics colloquia
- Analysis Group seminars
Applied Mathematics
- Applied Mathematics seminars
Alumni
Whether you join us online or in person, when you graduate you become a member of the University's worldwide alumni community. Benefit from access to alumni clubs, the Saint Connect networking and mentoring platform, and careers support.
Ask a student
If you are interested in learning what it's like to be a student at St Andrews you can speak to one of our student ambassadors. They'll let you know about their top tips, best study spots, favourite traditions and more.
Entry requirements
- A 2.1 undergraduate Honours degree in Mathematics, Statistics or a closely related subject area. If you studied your first degree outside the UK, see the international entry requirements.
- You must be able to demonstrate English language proficiency. See English language tests and qualifications.
The qualifications listed are indicative minimum requirements for entry. Some academic Schools will ask applicants to achieve significantly higher marks than the minimum. Obtaining the listed entry requirements will not guarantee you a place, as the University considers all aspects of every application including, where applicable, the writing sample, personal statement, and supporting documents.
Application requirements
- CV
- personal statement (optional)
- two original signed academic references
- academic transcripts and degree certificates
For more guidance, see supporting documents and references for postgraduate taught programmes.
English language proficiency
If English is not your first language, you may need to provide an English language test score to evidence your English language ability. See approved English language tests and scores for this course.
Fees and funding
- UK: £12,030
- Rest of the world: £25,900
Before we can begin processing your application, a payment of an application fee of £50 is required. In some instances, you may be eligible for an application fee waiver. Details of this, along with information on our tuition fees, can be found on the postgraduate fees and funding page.
Scholarships and funding
We are committed to supporting you through your studies, regardless of your financial circumstances. You may be eligible for scholarships, discounts or other support:
Start your journey
Legal notices
Admission to the University of St Andrews is governed by our Admissions policy
Information about all programmes from previous years of entry can be found in the course archive.
Curriculum development
As a research intensive institution, the University ensures that its teaching references the research interests of its staff, which may change from time to time. As a result, programmes are regularly reviewed with the aim of enhancing students' learning experience. Our approach to course revision is described online.
Tuition fees
The University will clarify compulsory fees and charges it requires any student to pay at the time of offer. The offer will also clarify conditions for any variation of fees. The University’s approach to fee setting is described online.
Page last updated: 6 March 2025