(Full time / Part time) 2021 start
Data Science and Analytics for Health MRes
Coronavirus information for applicants and offer holders
We hope that by the time you’re ready to start your studies with us the situation with COVID-19 will have eased. However, please be aware, we will continue to review our courses and other elements of the student experience in response to COVID-19 and we may need to adapt our provision to ensure students remain safe. For the most up-to-date information on COVID-19, regularly visit our website, which we will continue to update as the situation changes www.leeds.ac.uk/covid19faqs
Overview
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. These skills will enable you to extract valuable empirical evidence to better understand the causes of disease, and more accurately predict and evaluate health outcomes and health service needs.
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 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.
The programme is 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.
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 commercialization.
HDRUK studentships
Following funding from Health Data Research UK (HDRUK) we are able to offer up to 10 fully-funded places over the next two years to students who have applied to study on the programme. The funding is open to UK and international students and will cover the cost of UK fees (£11,750) as well as offering a stipend of around £15,285 to cover living expenses.
This funding is awarded based on academic merit.
To apply for this studentship, download and complete an application form then submit this via email to pgcomp@leeds.ac.uk.
Deadline for applications: Friday 28 May 2021.
Course content
A distinctive feature of this course is the inclusion of extended periods of hands‐on data science practice working on applied and collaborative workplace‐based projects across a range of health and healthcare services. You will be under the supervision of service‐specific specialists and academic experts in the management, analysis and interpretation of health and healthcare data.
These projects will offer you the opportunities to:
apply, test and further refine your skills in data science and analytics
experience working within established data science teams addressing pressing and pertinent health and healthcare problems
develop invaluable transferable skills relevant to interdisciplinary team science
generate analytical tools, empirical findings, and evidence‐based insights with the potential to have tangible impacts on health and healthcare policy and practice.
Want to find out more about your modules?
Take a look at the Data Science and Analytics for Health (MRes) module descriptions for more detail on what you will study.
Course structure
The list shown below represents typical modules/components studied and may change from time to time. Read more in our Terms and conditions.
Modules
Year 1
Compulsory modules
- Workplace-based Research and Development Project - choose between the long (120 credits) or short (105 credits) form project modules (see below for further information)
- Data Science and Analytics for Causal Inference and Prediction 15 credits
- Principles of Data Science and Analytics 15 credits
- Machine Learning 15 credits
- Artificial Intelligence 15 credits
Optional modules (selection of typical options shown below)
Choose between a long or short form project. If you choose to study the short form 105 credit workplace-based project, you must also study and pass the Programming for Data Science module (15 credits).
- Workplace-based Data Science and Analytics Research and Development Project (Long Form) 120 credits
- Workplace-based Data Science and Analytics Research and Development Project (Short Form) 105 credits
- Programming for Data Science 15 credits
Learning and teaching
Campus‐based blended learning with workplace‐based research project supervision.
On this course you’ll be taught by our expert academics, from lecturers through to professors. You may also be taught by industry professionals with years of experience, as well as trained postgraduate researchers, connecting you to some of the brightest minds on campus.
Applying, fees and funding
Entry requirements
A bachelor degree with a 2:1 (hons) in computer science, science, technology, engineering, mathematics or a quantitative health discipline; or equivalent first‐hand work‐related experience in one or more quantitative science or healthcare settings assessed through APEL.
We accept a range of international equivalent qualifications. For more information please contact the Admissions Team.
English language requirements
IELTS 6.5 overall, with no less than 6.0 in any component. For other English qualifications, read English language equivalent qualifications.
Improve your English
International students who do not meet the English language requirements for this programme may be able to study our postgraduate pre-sessional English course, to help improve your English language level.
This pre-sessional course is designed with a progression route to your degree programme and you’ll learn academic English in the context of your subject area. To find out more, read Language for Engineering (6 weeks) and Language for Science: Engineering (10 weeks).
If you need to study for longer than 10 weeks, read more about our postgraduate pre-sessional English course.
How to apply
Application deadlines
Applicants are encouraged to apply as early as possible.
31 July 2021 – International applicants
31 July 2021 - UK applicants
This link takes you to information on applying for taught programmes and to the University's online application system.
If you're unsure about the application process, contact the admissions team for help.
Important information
Prior to being made an offer, you will be invited to attend an online interview in order to assess your suitability for this course. You do not need to have identified a work placement to apply for this course.
As part of your application you will need to include the following information:
- details of the organisation you hope to undertake your extended Workplace-Based Research and Development project (if known) including name, email address and telephone number of your contact
- two references (one academic, one professional)
- contact details (ie Skype handle) in order for us to organise the online interview.
Read about visas, immigration and other information in International students. We recommend that international students apply as early as possible to ensure that they have time to apply for their visa.
Admissions policy
Faculty of Engineering and Physical Sciences Postgraduate Admissions Policy 2021
Fees
- UK: £11,250 (total)
- International: £25,500 (total)
Read more about paying fees and charges.
Brexit
Visit our Brexit page for the latest information on the effect of the UK's exit from the EU on current students and applicants to the University.
For fees information for international taught postgraduate students, read Masters fees.
Part-time fees
Fees for part-time courses are normally calculated based on the number of credits you study in a year compared to the equivalent full-time course. For example, if you study half the course credits in a year, you will pay half the full-time course fees for that year.
Additional cost information
There may be additional costs related to your course or programme of study, or related to being a student at the University of Leeds. Read more about additional costs
Scholarships and financial support
If you have the talent and drive, we want you to be able to study with us, whatever your financial circumstances. There may be help for students in the form of loans and non-repayable grants from the University and from the government. Find out more at Masters funding overview.
HDRUK studentships
Following funding from Health Data Research UK (HDRUK) we are able to offer up to 10 fully-funded places over the next two years to students who have applied to study on the programme. The funding is open to UK and international students and will cover the cost of UK fees (£11,750) as well as offering a stipend of around £15,285 to cover living expenses.
This funding is awarded based on academic merit.
To apply for this studentship, download and complete an application form then submit this via email to pgcomp@leeds.ac.uk.
Deadline for applications: Friday 28 May 2021.
Career opportunities
On completion of this course, you will 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
We encourage you to prepare for your career from day one. That’s one of the reasons Leeds graduates are so sought after by employers.
You’ll have access to the wide range of careers resources and support from your Careers Service. You’ll have the chance to attend industry presentations, book appointments with qualified careers consultants and take part in employability workshops and webinars.
Our annual STEM Careers Fairs provide further opportunities to explore your career options with some of the UKs leading employers.
Find out more about the range of services we offer on the Careers Service website and visit MyCareer.leeds.ac.uk once you have registered as a student to access one to one support, events and job vacancies.
We encourage you to prepare for your career from day one. That’s one of the reasons Leeds graduates are so sought after by employers.
The Careers Centre and staff in your faculty provide a range of help and advice to help you plan your career and make well-informed decisions along the way, even after you graduate. Find out more at the Careers website.