Training vision

The UKRI Centre for Doctoral Training in Artificial Intelligence for Healthcare at Imperial focusses on healthcare applications of core AI to train AI PhDs and Clinical PhD Fellows. We will deliver training integrating the development of technical skills with an appreciation for approaches to human-in-the-Loop AI design that are socially and ethically acceptable. The term “AI” means for us the development of intelligent systems that embody a practical solution. Amongst contemporary AI approaches, Machine Learning methods have shown to yield powerful solutions which work in purely data-driven manners and link via data science to emerging biomedical research methodologies. However, practical solutions involving AI will require a broader approach and we will drive technical innovation by providing broad training for exploitation of multiple technological strategies within the broader realm of AI, including, Machine Learning, Logic-based, Computer Vision or Natural Language Processing methods.

Expert Mentors

The exposure of our students to our expert mentors in related areas such as computer vision (e.g. for digital pathology and diagnostics) as well as sensing and wearable technologies (e.g. mobile mental health and digital biomarkers) will enhance the depth of training we can offer. Ultimately, no technological progress can help patients unless it is transformed into a (regulated) product or service. The UKRI CDT in AI for Healthcare plays to the established strength of the investigators and the whole supervisory team in leading cross-disciplinary research spanning AI and healthcare. Students will have at least two supervisors one with AI and one with biomedical background, and the two supervisors will be normally from two different Faculties/Departments – thus following our tried-and-tested crossdisciplinary training tradition at Imperial. The Centre will leverage the research excellence of its 100+ participating potential PhD supervisors across Imperial and our partners.

Partnerships

We have partnered closely with patient-focused charities, NHS trusts and a range of industries to ensure that students are trained in how to entrepreneurially realise impact from their work and understand how to navigate the regulatory pathways. One approach to delivering this will be for our PhD students to form co-creation teams including world-leading AI researchers, clinicians across 3 NHS trusts through our Academic Health Science Centre (Imperial Healthcare NHS Trust, Royal Brompton & Harefield NHS Foundation Trust, Royal Marsden NHS Trust), industry stakeholders and patient organisation partners. Moreover, we will embed clinicians as Clinical PhD Fellows into the centre’s PhD cohorts to foster a shared understanding between individuals developing and applying AI approaches and those using the technology offering a unique level of cognitive diversity and complementary in skills that will stimulate students to learn from each other in our co-training groups create a unique environment for research and training.

Integrated Training

Our large and diverse PhD cohorts regular PhD students and clinical PhD Fellows will benefit from an integrated training program and the ability to offer our students a unique sandbox in which to build their PhD success from AI and Healthcare applications. This is enabled through a PhD co-creation process by pairing students with AI and healthcare supervisors as well as industry and healthcare partners. The up to 4-year long PhD training program is split into three phases that provide underpinning skill training (Foundation phase), research training (Research Phase) and finally drive PhD impact training (Impact phase). Student-led training will organise the cohort in co-training teams. Cohort cohesion after year 1 is maintained by regular cohort wide meetings, training events and activities. Our Clinical CDT Fellows will receive clinical career training as needed and organised through the Imperial Clinical Academic Training Office (CATO) which allows us to integrate Clinical Fellows seamlessly into the CDT cohort training. Thus, all students will be able to go through training together as one cohort. The unique cohort size enable us to harness economies of scale to develop a bespoke training program involving different domains, such as regulatory training via the NHS Digital Academy, or our start-up building and launch via partner Agorai, which would otherwise not have been possible.