Applications of Artificial Intelligence (AI) tools in the biosciences are rapidly expanding and bioscientists skilled in the methods and thinking in AI are in short supply. This programme aims to prepare bioscience graduates to become leaders in the application of AI methods in professional bioscience Research and Development workplace environments. It has been specifically designed to make AI and related computational techniques (machine learning, analysis of large data sets) accessible to biology and biomedical graduate students without any prior experience in computational methods.

No background in computational methods needed – Learn coding, advanced statistical methods, the handling of large data sets, and applications of AI tools across biology

Develop in demand technical skills for a field that is rapidly growing in importance

Strong emphasis of hands-on experience in computer labs and projects using Queen Mary’s high performance computing cluster, Apocrita

Be taught by experts in the field, actively engaged in research in this exciting new area - Programme Director Dr Axel Rossberg is co-organiser of the “Biodiversity, monitoring and forecasting” Special Interest Group at Turing

Queen Mary is a member of the Alan Turing Institute and host of the Digital Environment Research Institute (DERI), which is amongst the UK's leaders in the development and application of Artificial Intelligence

Our London location, the hub of the UK AI industry, will place you in prime position for getting a job in the sector when you graduate

Graduates of this program will be well-positioned to seize the abundant job opportunities in the rapidly growing field of Artificial Intelligence.

The program will provide abundant opportunities for students to network with peers who possess diverse interests and aspirations.

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.

Assessment

The programme will be assessed through an exciting and varied combination of essays, practical assignments, group projects, workshops and presentations.

The group projects are assessed on the data analysis code produced and the presentation of the project results in a report and an oral group presentation.