- 4 Core Taught, 2 Core Practical and 3 Optional Modules
- Teaching is through lectures, seminars, practical workshops, peer-to-peer learning, tutorials, and laboratory-based research projects.
- Assessments include essays, lab reports, poster and oral presentations, written and oral examinations and podcasts.
Frontier Techniques in Biomedical Research
(20CATs) * new for 21/22
Series of masterclasses on biomedical technologies delivered by academics and industry partners. Each session will be led by an expert with direct experience of the topic (e.g.; genomics, gene editing, chemical genetics, nanotechnologies etc.) and will consist of lectures, seminars, tutorials, laboratory demonstrations and literature review.
Essential & Transferable Research Skills
(30CATs) * new for 21/22
Students will develop research skills and appreciation of research integrity. The module will equip students with the necessary skills to develop research ideas, questions and hypotheses, and propose suitable methodologies to address these.
Physical Biology of the Cell
The module explores the basic physical concepts underlying the behaviour of biomolecules, dynamic cell processes, cellular structure and signalling events, and equips students for a research career at the interface of biology and physics.
Microscopy & Imaging
This module provides a foundation in the principles and applications of microscopy, starting with basics of light microscopy and progressing to state of the art super-resolution microscopy, electron microscopy and scanned probe microscopy. The module includes workshops on image analysis and seminars that cover the most recent developments in the field.
Laboratory Project 1 & Laboratory Project 2
(2 x 40CATs)
Two 12-week research projects in two distinct disciplines. In most cases, this will be a biology-focused project and one in either chemistry, physics, mathematics, engineering or computer science.
Statistics for Data Analysis
This module gives students a basic understanding of the statistical methods appropriate to data analysis in analytical science. Topics include: basic probability; error analysis and calibration; summarising data and testing simple hypotheses; statistical computing; experimental design and analysis of variance; sampling methods and quality control; simple analysis of multivariate data.
Programming for Biomedical Data Analysis
This module provides the foundations in programming in R. Students will learn basic principles of programming through learning-by-doing workshops and a series of mock exams with increasing complexity from one-line statements to multi-loop programs.
Molecular Biology: Principles & Techniques
This module provides students with a background in mathematics, statistics, computer science, engineering, physics or chemistry with a comprehensive understanding of the principles of molecular biology.
Mathematical Modelling for Biosystems
This module provides a basic understanding of the mathematics of ordinary differential equations and partial differential equations (ODEs and PDEs), how to solve elementary problems analytically, and how to solve them numerically on the computer using MATLAB.
This module introduces the student to the many facets of modern of mass spectrometry. Emphasis is placed both on the interpretation of spectra and on instrumental methods, covering modern methods of ionisation (including ESI and MALDI) and mass analysis (including orthogonal TOF and FT-ICR) and the use of linked methods such as GC/MS, HPLC/MS and tandem mass spectrometry. Practical sessions include practice at interpretation and experiments using various mass spectrometric techniques.