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UCL (University College London): Artificial Intelligence Enabled Healthcare
| Institution | UCL (University College London) View institution profile |
|---|---|
| Department | Institute of Health Informatics View department profile |
| Web | https://www.ucl.ac.uk/population-health-sciences |
| Study type | Taught |
Summary
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.
Master of Research - MRes
| Level | RQF Level 7 |
|---|---|
| Entry requirements | A minimum of an upper second class honours undergraduate degree, or a Master's degree in a relevant discipline (or equivalent international qualifications or experience). Our preferred subject areas are Physical Sciences (Computer Science, Engineering, Mathematics and Physics) or Clinical / Biomedical Science. Applicants with a clinical background or degree in Biomedical Science must be able to demonstrate strong computational skills. You must be able to demonstrate an interest in creating, developing or evaluating AI-enabled Healthcare systems. English level: Level 2 |
| Location | London, Bloomsbury Gower Street Camden WC1E 6BT |
| Level | RQF Level 7 |
|---|---|
| Entry requirements | A minimum of an upper second class honours undergraduate degree, or a Master's degree in a relevant discipline (or equivalent international qualifications or experience). Our preferred subject areas are Physical Sciences (Computer Science, Engineering, Mathematics and Physics) or Clinical / Biomedical Science. Applicants with a clinical background or degree in Biomedical Science must be able to demonstrate strong computational skills. You must be able to demonstrate an interest in creating, developing or evaluating AI-enabled Healthcare systems. English level: Level 2 |
| Location | London, Bloomsbury Gower Street Camden WC1E 6BT |
| Level | RQF Level 7 |
|---|---|
| Entry requirements | A minimum of an upper second class honours undergraduate degree, or a Master's degree in a relevant discipline (or equivalent international qualifications or experience). Our preferred subject areas are Physical Sciences (Computer Science, Engineering, Mathematics and Physics) or Clinical / Biomedical Science. Applicants with a clinical background or degree in Biomedical Science must be able to demonstrate strong computational skills. You must be able to demonstrate an interest in creating, developing or evaluating AI-enabled Healthcare systems. English level: Level 2 |
| Location | London, Bloomsbury Gower Street Camden WC1E 6BT |
| Level | RQF Level 7 |
|---|---|
| Entry requirements | A minimum of an upper second class honours undergraduate degree, or a Master's degree in a relevant discipline (or equivalent international qualifications or experience). Our preferred subject areas are Physical Sciences (Computer Science, Engineering, Mathematics and Physics) or Clinical / Biomedical Science. Applicants with a clinical background or degree in Biomedical Science must be able to demonstrate strong computational skills. You must be able to demonstrate an interest in creating, developing or evaluating AI-enabled Healthcare systems. English level: Level 2 |
| Location | London, Bloomsbury Gower Street Camden WC1E 6BT |
Make your Population Health Master’s matter
Join a world-leading faculty tackling today’s most urgent health challenges – and take your Master’s further, wherever your career leads.
At UCL’s Faculty of Population Health Sciences, you’ll deepen your expertise and gain the critical thinking, practical skills, and interdisciplinary insight employers value across the health sector.
- Study at the ninth best university in the world (QS World Rankings 2026) and join a faculty ranked #3 globally for public health (ShanghaiRankings 2024).
- Ranked #1 in the UK for research power in medicine, health and life sciences (REF 2021), …
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