Artificial Intelligence in the Biosciences MSc

Queen Mary University of London

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 biologyDevelop in demand technical skills for a field that is rapidly growing in importanceStrong emphasis of hands-on experience in computer labs and projects using Queen Mary’s high performance computing cluster, ApocritaBe taught by experts in the field, actively engaged in research in this exciting new area - Programme Director Dr Mohamed Elbadawi research centres on the use of digital technologies to advance healthcare, including machine learning, robotics and 3D printingQueen 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 IntelligenceOur London location, the hub of the UK AI industry, will place you in prime position for getting a job in the sector when you graduateGraduates 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 aspirationsWhat you'll studyThis 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.

School of Electronic Engineering and Computer Science