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PhD opportunities at the UKRI Centre Artificial Intelligence for Healthcare

Qualification Type: PhD
Location: London
Funding for: UK Students, EU Students, International Students
Funding amount: see advert text
Hours: Full Time
Placed On: 21st November 2019
Closes: 6th February 2020

Our vision is to establish new-generation innovators in Artificial Intelligence (AI) applied to Healthcare. For the Academic Year 2020-21, we aim to recruit 25+ PhD students including a number of clinical PhD Fellows.

We take the view that AI is ultimately a question about how to realise artificial systems that solve problems presently requiring human intelligence to solve (e.g. problems solved by clinicians, nurses and therapists). The contemporary answer to the AI research question is machine learning, i.e. learning how to solve the problem from experience instead of programming it. Learning in turn requires data, which extends our view of AI to encompass also data science and data engineering. However, AI in our Centre implies an entire system that solves a practical (healthcare) problem, this may require combining different algorithmic and representational approaches that encompass machine learning, robotics, optimisation, symbolic reasoning, natural language processing, and computer vision.

AI in Healthcare contains all the elements that makes AI a hard problem. AI is hard because systems have to be able to cope with unexpected circumstances when solving perceptual, reasoning or planning problems (e.g. due to the diversity and variability of human nature). Moreover, while many AI systems can solve simple or restricted problems (e.g. in video games), they often fail when scaled up to more general settings and cannot operate with unusual situations and adjust accordingly. Thus, AI in healthcare needs and drives current AI research avenues such as interpretable AI, privacy-preserving learning, trust in AI, data-efficient learning and safety in autonomy. These are key due to the immediate impact on life and health for users depending on AI for healthcare support. Thus, AI training in our Centre will generalise across a whole spectrum of AI application scenarios far beyond healthcare.

Tackling healthcare challenges requires learning how to bridge our understanding of the clinical language and methodologies, regulatory, legal and ethical frameworks of healthcare with core AI technical skills. Our training outcomes are AI researchers who have learned to move fluidly across the disciplinary AI/healthcare boundaries and can develop and implement deployable solutions. Crucially, we will empower our alumni through our unique training program to become independent actors in the highly regulated healthcare technology market and enable them to consolidate their impact through our NHS partnerships and globally through our international industrial partners so as to become part of the long-term legacy of our UKRI Centre.

What to expect

The doctoral researchers will benefit from an integrated training program and the joint supervision between at least one AI expert supervisor and one Healthcare expert supervisor. Our supervisor pool comprises world-leading experts in Artificial Intelligence and closely related disciplines (such as computer vision and robotics) as well as clinicians from three NHS Trusts that treat over 2 Million patients a year (Imperial Healthcare NHS Trust Royal Brompton & Harefield NHS Foundation Trust, and Royal Marsden NHS Trust). The clinical supervisors and healthcare partners span the full breadth of healthcare challenges facing society, such as dementia, brain and mental health, infectious diseases, cancer and surgery, obesity and diabetes, cardiovascular and lung diseases, intensive care and primary care. Our NHS healthcare partners provide care for a significant proportion of London’s general and specialist healthcare needs and we have embedded the centre in Imperial’s unique data ecology to gain access and process these data sets and deploy them through our secondary and primary care partners (covering North-West London).

We have a ‘gold-standard’ pipeline and vast network of research partners to provide access to data and to deploy technology in these highly regulated clinical worlds. Our PhD training programme is split into three phases: underpinning skills and knowledge in the Foundation phase, doing research in the Research Phase and driving PhD impact in the Impact phase; it also comprises student-led training which complements masterclasses and workshops in commercialisation of research, medical technology regulation and clinical trial of technology. There will be very many opportunities to showcase the projects at national and international conferences and public engagement events. Our students will also undertake research visits and internships with industry partners.

Who should apply?

We are looking for graduates who are enthusiastic and strongly motivated to combine their AI-related skills with a strong interest in healthcare and patient treatment.  Normally, applicants should have a degree in a relevant scientific or technical discipline, such as computer science, engineering (mechanical, electrical/electronics, bio/biomedical), mathematics, physics, as well as biological sciences, psychology, physiology or medicine. Desirable skills include mathematics, statistics, machine learning, computer vision, deep learning, robotics, natural language processing, human-computer interfaces and software engineering.

We welcome applications from UK and EU students in particular. Normally, to be eligible, applicants must have no restrictions on how long they can stay in the UK and have been ordinarily resident in the UK for at least 3 years prior to the start date of the studentship.

How to Apply

For the Academic Year 2020-21, we have 25+ funded PhD places including clinical PhD Fellows. We are recruiting in two rounds: the application deadline of Round One is 24 December 2019. The application deadline of Round Two is is 6 February 2020.

Please check on our webpage what information and documents must be included in your application. The please apply through the Imperial application portal: the login page and guidance on how to apply can be found on this page:


Each studentship award covers UK/EU tuition fees and a stipend for three years. For non-clinical PhD students, the stipend is paid at the UKRI rate plus London weighting (e.g. in 2019-20 the annual stipend rate was £17,009, tax-free). Clinical PhD Fellows are paid at their current basic clinical salary level, without banding, details tbc.


For any queries, please contact the Centre Manager at or visit our website.