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, one-to-one discussion and practical computer sessions.
Class sizes
From 10 to 60 students.
Dissertation
An end-of-course three-month research activity with ongoing support culminating in a 15,000-word dissertation.
Assessment
A mix of exams, coursework, tests, presentations, research essays and a research project.
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 in your year of study.
Optional modules are subject to change each year, require a minimum number of participants to be offered, and some may only allow a limited numbers of students. Not all optional modules are available in each semester and some modules are subject to pre-requisites being satisfied. Read the University's position on curriculum development for more information.
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.
Course information may change. Module information and course content, teaching and assessment may change each year and after you have accepted your offer to study at the University of St Andrews. We display the most up-to-date information possible, but this could be from a previous academic year. For the latest module information, see the module catalogue.
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- Advanced Computational Techniques: studies several ideas and techniques that underpin modern numerical treatment of processes described by partial differential equations.
- Dissertation for MSc Mathematical Biology
- 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.
- 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.
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- 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.
- Advanced Bayesian Inference
- Applied Bayesian Statistics
- 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.
- Computing in Statistics: teaches computer programming skills, including principles of good programming practice, with an emphasis on statistical computing.
- Fluid Dynamics: introduces the theory of incompressible fluid dynamics, with particular attention to conservation laws.
- Independent Study Module
- Machine Learning: This module covers the essential theory and algorithms of Machine Learning, including mathematical foundations and methodological approaches.
- Machine Learning for Data Analysis: This module covers many of the methods found under the banner of Datamining, building from a theoretical perspective but ultimately teaching practical application.
- 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.
- Professional Skills for Mathematical Scientists
- Symbolic Artificial Intelligence: The module gives an overview of traditional AI methods and the philosophy of AI.
- Uncertainty in Artificial Intelligence: This module covers reasoning and decision making in the presence of uncertainty.
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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.
Application requirements
- CV or résumé
- personal statement (optional)
- one original signed academic reference
- academic transcripts and degree certificates that confirm your current or final marks. If your transcripts are not in English, please provide certified translations. Do not send original documents as they cannot be returned.
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: £12,630
- Rest of the world: £27,200
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:
Contact us
- Postgraduate online information events
- The School can help with course content, teaching and other topics: ask the School
- Ask University Admissions about how to apply, fees, scholarships and other topics
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: 27 May 2026