Course summary
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 program aims to prepare bioscience graduates to become leaders in the application of AI methods in professional bioscience R&D 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
Entry requirements
A 2:1 or above at undergraduate level in a Science subject such as Biology, Chemistry, Mathematics or a related subject. Other routes: Applicants with a 2:2 degree may be considered on an individual basis provided there is relevant experience.
Fees and funding
Tuition fees
No fee information has been provided for this course
Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .
Additional fee information
Provider information
Queen Mary University of London
Admissions and Recruitment Office
Mile End Road
Tower Hamlets
London
E1 4NS