Artificial Intelligence in the Biosciences MSc

This multifaceted programme builds the knowledge and skills needed to kick-start your career in professional bioscience research, consulting, and development. Teaching is jointly delivered by experts in the School of Biological and Behavioural Sciences and The School of Mathematical Sciences and will cover areas such as applications of AI and Data Science in Biology, Ecology and Biomedicine and skills such as analysis of large data sets, coding, and statistics.

In Semester A you will cover modules on essential shell command and HPC usage, coding, its use for statistical data analysis, and then an introduction to AI concepts, while also discussing applications in bioinformatics.

In Semester B you’ll be introduced to the full range of applications of AI in the biosciences, covering both established methods and latest cutting-edge developments and trends. You will also cover modern computation-intensive statistical methods.

In Semester C, you will carry out two group projects, solving problems in the biosciences using AI methods to develop your AI knowledge into professional skills. The task in the first project is well defined, so you can focus on learning how to structure a problem to approach it efficiently as a group. Then, for the second project you will be given a more widely defined bioscience problem, emulating a typical work-place situation.

Graduates of this program will have a distinct competitive advantage in seeking employment. Not only do they demonstrate that they can cross traditionally distant disciplines but they also will show that they understand the applications of AI to biology and biomedicine. The data analysis and coding skills that we teach are highly sought after not only by employers in the areas of biology and biomedicine, but across a wide range of sectors. 

Graduates will find employment opportunities throughout the agro- and biotechnology industry, pharmaceutical companies, universities, medical research institutes, in governmental agencies, in non-profit organisations, and as data scientists, software engineers or consultants in a wide range of sectors. 

Potential employers are invited to participate in the group project presentation seminars in Semester C and arrangements are made for networking between employers and students after the presentations.