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Data Science and AI for Health Innovation MRes

University of Liverpool

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University of Liverpool

Course options

4 options available

  • Qualification

    MRes - Master of Research

  • Location

    Liverpool Campus

  • Study mode

    Full time

  • Start date

    28-SEP-26

  • Duration

    12 Months

Course summary

Healthcare is increasingly driven by data science, artificial intelligence and digital innovation. From electronic health records and genomics to AI-assisted diagnostics and learning health systems, healthcare organisations now generate vast amounts of data with enormous potential to improve patient care, healthcare delivery and public health outcomes. As the use of healthcare data and AI continues to expand, there is growing demand for researchers and professionals who can analyse, interpret and apply complex data responsibly, ethically and effectively. The MRes Data Science and AI for Health Innovation combines advanced methodological training with a substantial independent research project, enabling students to develop both specialist technical expertise and strong research capability. Students build expertise in statistics, programming, machine learning, prediction modelling and healthcare evaluation while gaining practical experience conducting independent research within a supportive and collaborative academic environment. Designed around flexibility, innovation and practical application, the programme also allows students to tailor their studies through optional modules aligned to their own research interests and career ambitions. The programme has strong links with the Civic Health Innovation Labs (CHIL), an internationally recognised multidisciplinary research centre based at the University of Liverpool. CHIL brings together experts from academia, the NHS, local government, charities and industry to develop responsible approaches to data use and AI for health and society. Students benefit from exposure to real-world healthcare challenges, research collaborations and emerging developments in responsible AI and healthcare innovation. Graduates from the programme are well placed for PhD study and research-focused careers across healthcare, academia, digital health, pharmaceutical research, public health and healthcare innovation. Why study this programme Develop advanced research expertise The programme combines specialist training in statistics, programming, machine learning and AI with extensive independent research experience. You will develop the methodological and analytical expertise needed to contribute to cutting-edge healthcare research and innovation while building strong foundations for future research or doctoral study. Conduct a substantial independent research project A major component of the programme is an extended supervised research project, allowing students to apply advanced analytical approaches to real-world healthcare questions. You will work closely with experienced academic supervisors and research teams while developing valuable practical experience in designing, conducting and communicating research. Tailor your learning to your interests Optional modules allow students to explore specialist areas aligned to their own interests and future ambitions, including machine learning, causal inference, healthcare evaluation and statistical genetics. This flexibility helps you to develop a distinctive methodological profile suited to a wide range of research and professional pathways. Learn from experts working at the forefront of health innovation You will study alongside approachable staff with expertise across statistics, health data science, artificial intelligence and healthcare research. Teaching is enriched by collaborations with organisations including the NHS, industry and the Civic Health Innovation Labs (CHIL), helping students connect advanced methodological learning to real-world healthcare innovation.

Application deadline

11/09/2026

Tuition fees

Students living in United States
(International fees)

£ 2,683month

Tuition fees shown are for indicative purposes and may vary. Please check with the institution for most up to date details.

University information

University image

University of Liverpool

University of Liverpool

  • University League Table

    22nd

  • Campus address

    Main Site, The Foundation Building, Brownlow Hill, Liverpool, Liverpool, L69 7ZX, United Kingdom

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Subject rankings

  • Subject ranking

    Business & Management Stu

    22nd out of 124 4

    28th out of 118

  • Entry standards

    / Max 212
    131 62%

    33rd

  • Graduate prospects

    / Max 100
    80.0 80%

    21st

    4

  • Student satisfaction

    / Max 4
    3.19 80%

    43rd

    2

  • Entry standards

    / Max 229
    135 59%

    35th

  • Graduate prospects

    / Max 100
    87.0 87%

    25th

    13

  • Student satisfaction

    / Max 4
    3.09 77%

    47th

    21

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