Artificial Intelligence Enabled Healthcare MRes

UCL (University College London)

Artificial Intelligence (AI) has the potential to transform health and healthcare systems globally, yet few individuals have the required skills and training. To address this challenge, the Artificial Intelligence Enabled Healthcare MRes will create a unique interdisciplinary environment to train the brightest and best healthcare artificial intelligence scientists and innovators of the future.The Artificial Intelligence Enabled Healthcare MRes is a one-year stand-alone course (with a two-year part-time option) that provides training and support in advanced research and practical skills for future researchers or healthcare professionals to fit in the modern clinical environment that requires AI and health data science skills. The course covers the core competencies of artificial intelligence and has a central emphasis on how healthcare organisations work. Ethical training for medical artificial intelligence will be explicitly emphasised alongside a broader approach to responsible research and innovation. During the course, you will learn the statistical underpinnings of machine learning theory, get a practical grounding in research software engineering and the principles of healthcare and medical research, develop relationships between academia and the NHS, as well as a thorough treatment of topics in machine learning, statistics and principles of data science. As part of the MRes, alongside the core and elective modules, you will complete a substantial Master's-level project of your choice, working with a supervisory team that consist of a group of clinicians and academics. As a cohort of the MRes programme, students will also participate in a range of seminars, training programmes, placements and other activities at UCL’s Institute of Health Informatics (UCL IHI).The MRes programme is for students with an interest in creating and developing AI solutions that transform and solve healthcare challenges. The programme is ideal for students keen to develop clinical knowledge and algorithmic and programming expertise.

Population Health Sciences