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MRes Data Science and Analytics for Health

  • DeadlineStudy Details:

    12 months full time
    24 months part time

Course Description

This course is open to NHS Digital staff only.

From understanding diseases better to improving the appointment process, data science and analytics are integral to the way the healthcare system works in society today.

Our Data Science and Analytics for Health MRes degree provides a comprehensive training in the management, modelling and interpretation of health and healthcare data used by clinical, behavioural and organisational sources.

The course draws on recent advances in information technology, data management, statistical modelling (for description/classification, causal inference and prediction), machine learning and artificial intelligence. It’s designed to enable you to develop both the technical and applied skills required for addressing real‐world challenges in real‐world health and healthcare contexts.

Entry Requirements

Either a 1st class degree at bachelor or masters level Or 2:1 (hons) plus (minimum 3 years) first‐hand work‐related experience in one or more quantitative science or healthcare settings.

Fees

See our website for fees

Student Destinations

Data science and analytics have become key to streamlining the workings of many businesses – especially in healthcare. The healthcare industry looks after huge data sets so rely on qualified data scientists to provide practical insights and help contribute to improving the way the health system works in general. And this demand is only going to grow.

This MSc will give you the advanced and technical skill set in this field that’s in demand across the healthcare industry – and beyond.

Plus, the University of Leeds is in the top five most targeted universities in the UK by graduate recruiters, according to High Fliers’ The Graduate Market in 2022 report.

On completion of this course, you’ll be strongly positioned to enter an exciting and rewarding career path in one of at least three main areas:

  • as skilled data science researchers in research‐intensive settings (including academia) – with good research funding prospects and substantial potential for societal and economic impacts arising out of the outputs from your applied, workplace‐based health data science projects;
  • as health and healthcare data science entrepreneurs – developing business ideas based on the application of your advanced data science skills in extended workplace‐based research projects within the health domain; and
  • as key research and development staff within public, private/commercial or voluntary sector organisations – generating and capitalising upon the novel insights and discoveries accessed through the application of advanced data science techniques to rapidly expanding clinical, behavioural and operational data sets.

Careers support

At Leeds, we help you to prepare for your future from day one. Our wide range of careers resources — including our award-winning Employability team — are on hand to offer guidance and support, ensuring you are prepared to take your next steps after graduation and get you where you want to be.

  • Employability events — we run a full range of events including careers fairs in specialist areas and across broader industries — all with employers who are actively recruiting for roles.
  • MyCareer system — on your course and after you graduate, you’ll have access to a dedicated careers portal where you can book appointments with our team, get information on careers and see job vacancies and upcoming events.
  • Qualified careers consultants — gain guidance, support and information to help you choose a career path. You’ll have access to 1-2-1 meetings and events to learn how to find employers to target, research before interviews and brush up on your interview skills.
  • Opportunities at Leeds — there are plenty of exciting opportunities offered by our Leeds University Union, including volunteering and over 300 clubs and societies to get involved in.

Module Details

This course recognises and utilises recent advances in information technology, data management, statistical modelling (for description/classification, causal inference and prediction), machine learning and artificial intelligence. It intends to equip health data scientists and health data analysts with the skills required to: harness the empirical insights available within large and varied data sources; and apply these to pressing clinical, social and organisational questions within the broad and varied context of health and healthcare services.

This course draws together:

  • established expertise in applied data science relevant to the statistical modelling of complex data and the use of machine learning and artificial intelligence to accelerate the application of modelling for insight and discovery through causal inference and prediction
  • key public and private sector partners with extensive experience of managing a range of complex health and healthcare data sources, and harnessing these to inform professional practice, service delivery, public policy and commercialisation.

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