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MSc Biomathematics
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Objectives
To enhance the general skills of students (including IT skills, presentation skills, problem solving abilities, numeracy and their ability to retrieve information in an efficient manner.) To offer students the opportunity to study the applications of mathematics to biology to an advanced level within an environment informed by current research. To provide students with advanced training that will be of use in a career as a worker in the general area of Mathematics applied to biology. To provide students with training in the preparation of reports involving mathematical and biological material, including correct referencing, appropriate layout and style. To provide students with a research-type experience that will aid them in their approach to further research activity. To provide students with information that will help them to make an informed judgement as to the appropriate methods to employ when analysing a problem of mathematics applied to biology.
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Entry requirements
Entry Qualifications BSc degree, of Upper Second class standard or above, in Mathematics, Physics, Computing, Engineering or related subjects (or an equivalent qualification). Knowledge of a computer programming language would be an advantage, but is not essential. Language requirements: IELTS 6.0 or TOEFL 540 (200) or comparable.
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Academic title
MSc Biomathematics
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Course description
Course Description
The MSc in Biomathematics looks at quantitative techniques in biology and medicine that have lead to a demand for interaction between researchers in biology and those with mathematical/computational skills.
Modules and Options
The lists of modules below represent the range of options available for each year of study. This may not be a complete list of the options you will study, and may be subject to change, so please contact the department for further details.
Stage 1
Compulsory: GENE TECHNOLOGY
Compulsory: MATHEMATICAL BIOLOGY
Compulsory: MATHEMATICAL RESEARCH TECHNIQUES USING MATLAB
Compulsory: ORDINARY DIFFERENTIAL EQUATIONS
Compulsory: STOCHASTIC PROCESSES
Core: BIOMATHEMATICS DISSERTATION
Core: RESEARCH METHODS
LINEAR MODELS
MACHINE LEARNING AND DATA MINING
QUANTITATIVE NEUROSCIENCE
Teaching and Assessment Methods
A: Knowledge and Understanding
Learning Outcomes
A1 : A range of ideas concerning biomathematics and its applications, including methods appropriate in specialized applications and some knowledge of relevant probabilistic/statistical/computing ideas.
A2 : How to formulate algorithms to solve problems.
A3 : Experiencing the power of efficient computer programs.
A4 : Some of the ways in which apparently disparate parts of the subject may interconnect.
A5 : Understand background behind various experimental techniques used by biologists.
A6 : One or more current areas of research in biomathematics, including an awareness of the development of these areas of research.
Teaching Methods
A1-A4 are principally acquired through the coherent programmes of lectures, exercises and problem classes. These are supplemented, where appropriate, by the use of computers, computer packages, textbooks, handouts and on-line material.
In most courses there is regular set work. This work is marked and this process informs the course teacher of common difficulties that require extra attention during the subsequent problem classes.
A5 is principally acquired through exposure to the techniques in BS932
A6 is principally acquired through the preparation of an essay and a thesis on specialized topics. During the production of their written work, students are expected to extend and enhance the basic course material concerning internet searching and the production of mathematical texts. The research guidance during the summer is a critical aspect of this training.
Assessment Methods
Knowledge and understanding are assessed through coursework, examinations, essays and the summer dissertation.
B: Intellectual/Cognitive Skills
Learning Outcomes
B1 : Analyse a mass of information and carry out an appropriate analysis of the problem material.
B2 : Express a biological problem in mathematical terms and carry out an appropriate analysis.
B3 : Reason critically and interpret information in a manner that can be communicated effectively.
B4 : Integrate and link information across course components.
B5 : Under guidance of a supervisor, plan and carry out a piece of research and present the results in a coherent fashion.
Teaching Methods
B1-3 These skills are developed through the regular coursework exercises - which often have specific biological content, due to the stranding arrangements. In seeking to answer these exercises students become accustomed to identifying key facts in a body of information. The problems classes provide back-up as required.
B4-5 These skills are initiated during the course of the preparation of the essay and are further developed during the course of the summer project.
Assessment Methods
The level of attainment of these skills is assessed through the routine work, coursework, the summer examinations, and through examination of the summer project.
C: Practical Skills
Learning Outcomes
C1 : Model biological problems using mathematics.
C2 : Construct and use algorithms.
C3 : Use computer programmes and/or packages
C4 : Use a mathematical word-processing package
C5 : Make an effective literature search
C6 : Prepare a technical report
C7 : Give a presentation and defend their ideas in an interview.
C8 : Gain experience of experimental techniques used by biologists.
Teaching Methods
C1-C2 are developed through the programme of lectures, regular exercises and computer work.
C3-C7 are developed during the course of the preparation of the essay and the thesis.
C8 are acquired through practical sessions
Assessment Methods
C1-C2 is assessed by the regular coursework and examinations.
C3 is assessed in this way and also by any computer output that forms part of the summer project
C4-C7 are assessed through the essay and summer thesis.
C8 is assessed through BS932
D: Key Skills
Learning Outcomes
D1 : Write and/or present work clearly and effectively.
D2 : Use computer packages and/or programming languages for data analysis and/or computation.
D3 : Enhance existing numerical ability
D4 : Choose the appropriate method of inquiry in order to address a range of practical and theoretical problems in biomathematics.
D5 : Learn from feedback and respond appropriately and effectively to supervision and guidance. This is particularly important in the experimental lab, due to the lack of prior experiences of this environment.
D6 : Work pragmatically to meet deadlines.
Teaching Methods
D1 is promoted by the supervisor of the essay and thesis work and by class teachers' feedback on written solutions to problems. It is further promoted through the student giving presentations to separate audiences of mathematicians and biologists.
D2 results from the coursework associated with various lecture courses.
D3 is a natural consequence of courses with high numeric content.
D4 is a consequence of the coursework, problems classes, lectures and laboratory work.
D5-6 result from a tightly timetabled course of lectures and submission dates that require the student to effectively organise time to meet deadlines.
Assessment Methods
Key skills are assessed throughout the degree via coursework, examinations, the essay and the summer project.
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