Date of entry

September 2027

Teaching

We use a variety of teaching methods, including:

  • lectures
  • lab practicals
  • workshops
  • tutorials
  • computer-based learning
  • media and video exercises
  • field excursions where appropriate

Assessment

We use a combination of in-course and end-of-course assessments. These will take the form of:

  • practical reports (based on lab work)
  • computer-based exercises
  • data processing exercises
  • essays
  • exams

Modules

Core Modules

These modules are an essential part of your course.

Module code: BS11008 Credits: 20 Semester: Semester 1

This module equips you to operate safely within a bioscience laboratory. You will work, with appropriate guidance, on a range of practical protocols to successfully employ basic bioscience techniques.

Optional Modules

You need to choose one or more of these modules as part of your course.

Module code: BS11005 Credits: 20 Semester: Semester 1

​​A strong foundation in the physical sciences is essential for biological and biomedical courses. 

​You will build your skills in biophysics, inorganic and physical chemistry, and numeracy. You will focus on how these apply to the life sciences. 

​You will develop these skills through practical classes, lectures and workshops.

Core Modules

These modules are an essential part of your course.

Module code: BS21001 Credits: 10 Semester: Semester 1

​​Statistics and experimental design are fundamental to every branch of the life sciences. 

​You will learn how to analyse biological and biomedical datasets. You will also learn to design robust experiments, and draw meaningful conclusions from data. 

​You will also cover topics like: 

  • ​Hypothesis testing 
  • ​ANOVA 
  • ​Regression 
  • ​Data visualisation​ 

Optional Modules

You need to choose one or more of these modules as part of your course.

Module code: BS21010 Credits: 20 Semester: Semester 1

​​Programming is becoming an essential skill for modern life scientists. 

​This module gives you a hands-on introduction to Python 3. This will cover the core concepts of programming such as: 

  • ​variables and control statements 
  • ​functions, data structures and file handling 

​You will also explore Biopython. This is designed for working with biological data. You will also develop the practical skills to write and test your own Python scripts for problem solving and data analysis.

Core Modules

These modules are an essential part of your course.

Module code: BS30007 Credits: 80 Semester: Both Semester 1 and 2

This module comprises a year in a Life Sciences-relevant industry, where you will gain skills and understanding from being embedded in a real workplace setting.

Optional Modules

You need to choose one or more of these modules as part of your course.

Module code: BS32049 Credits: 20 Semester: Semester 2

This module gives you a thorough grounding in immunology, from the cells and tissues of the immune system to how they coordinate responses against pathogens.

You will also explore the clinical consequences when these responses go wrong, including allergy, autoimmunity and inflammatory diseases

Core Modules

These modules are an essential part of your course.

Module code: BS41010 Credits: 60 Semester: Semester 1

This capstone module is the major research experience of your Honours degree.

You will conduct an independent research project within the University's research environment under the guidance and supervision of a research academic and develop the skills necessary to formulate and conduct a research project, and to communicate it via a dissertation of up to 6,000 words, and at an Honours symposium alongside the wider research community.

Optional Modules

You need to choose one or more of these modules as part of your course.

Module code: BS42029 Credits: 20 Semester: Semester 2

​This module introduces you to machine learning in a biological context.

You will explore key concepts in machine learning for biological data analysis, study current approaches through seminars and guided self-study, and develop your ability to critically evaluate the use of AI tools in biology alongside their ethical implications.​

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