Mathematical Biology (MSc) 2023 entry

This MSc prepares students with a background in mathematics and related fields for a PhD in Mathematical Biology or a research career in the biomedical sector. A wide range of topics are covered including mathematical oncology, ecological modelling, medical statistics, and population dynamics.

Start date
September 2023
End date
September 2024
Duration
One year full time
School
School of Mathematics and Statistics

Application deadline

Thursday 10 August 2023

Applicants should apply as early as possible to be eligible for certain scholarships and for international visa purposes.

Entry requirements

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.

Course details

The MSc in Mathematical Biology consists of two semesters of taught courses run by the School of Mathematics and Statistics, followed by a dissertation undertaken over the summer months. 

There is a growing worldwide demand for students with these skills in mathematical biology academic research, as well as in the life sciences industrial sector, including biotechnology, biomedical, healthcare and pharmaceutical companies. 

Highlights 

  • You will take a course of study tailored to your interests. 
  • You will be exposed to modern and relevant ideas in mathematical biology. 
  • You will be prepared to pursue a PhD and academic career in mathematical biology. 
  • You will acquire the qualifications and skills for a career in the biomedical sector. 

Modules

The modules in this programme have varying methods of delivery and assessment. For more details about each module, including weekly contact hours, teaching methods and assessment, please see the latest module catalogue, which is for the 2022-2023 academic year; some elements may be subject to change for 2023 entry. 

  • 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. 

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. 
  • Computing in Mathematics: 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. 
  • Population Genetics: discusses how the frequencies of characteristics in large natural populations can be explained using mathematical models and how statistical techniques may be used to investigate model validity.

Optional modules are subject to change each year and require a minimum number of participants to be offered; some may only allow limited numbers of students (see the University's position on curriculum development). 

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. 
  • Design of Experiments: introduces a wide range of features that occur in real comparative experiments with applications including trials of potential new medicines by the pharmaceutical industry. 
  • 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. 

Optional modules are subject to change each year and require a minimum number of participants to be offered; some may only allow limited numbers of students (see the University's position on curriculum development). 

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.  

If students 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. By choosing an exit award, you will finish your degree at the end of the second semester of study and receive a PGDip instead of an MSc. 

The modules listed here are indicative, and there is no guarantee they will run for 2023 entry. Take a look at the most up-to-date modules in the module catalogue.

Teaching

Class sizes range from 10 to 60 students, depending on the module.

Most modules for the MSc in Mathematical Biology are semester-long lecture courses with end-of-semester exams, and some modules have a large element of continuous assessment.

The School of Mathematics and Statistics is well equipped with computing facilities (including a large parallel computing cluster) and an on-site library. 

Events

There are a number of different seminars held each week in the School of Mathematics and Statistics. These include: 

Pure Mathematics 

Applied Mathematics 

Statistics 

Fees

Home
£11,120

Overseas
£23,530

More information on tuition fees can be found on the postgraduate fees and funding page.

Funding and scholarships

The University of St Andrews is committed to attracting the very best students, regardless of financial circumstances. Find out more about the scholarships and postgraduate loans available.

All taught postgraduate scholarships

After your degree

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: 

  • bio-pharmaceutical companies 
  • medical devices companies 
  • life-sciences industry. 

Recent Masters and Doctoral students in the School of Mathematics and Statistics have been employed at some of the best universities and most well-known companies around the world. 

The Careers Centre offers one-to-one advice to all students as well as a programme of events to assist students in building their employability skills.


Further study

The MSc in Mathematical Biology prepares students for further postgraduate studies in mathematical biology research.

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. 

The School of Mathematics and Statistics has active research groups in: 

  • Applied Mathematics (Vortex Dynamics Group, Solar and Magnetospheric Theory Group, Mathematical Biology Group) 
  • Mathematical Biology (Mathematical Oncology, Cell Migration and Tissue Growth) 
  • Pure Mathematics (Analysis Group, Algebra and Combinatorics Group) 
  • Statistics (Statistical Ecology, Statistical Medicine and Molecular Biology, and Statistical Methodology). 
Postgraduate research

What to do next

Online information events

Join us for one of our information events where you can find out about different levels of study and specific courses we run. There are also sessions available for parents and college counsellors.

Postgraduate virtual days

We encourage all students who are thinking of applying to the University to attend one of our online visiting days.

Contact us

Phone
+44 (0)1334 46 2344
Email
maths-msc-enquiries@st-andrews.ac.uk
Address
School of Mathematics and Statistics
Mathematical Institute
North Haugh
St Andrews
KY16 9SS

School of Mathematics and Statistics website