What Our Master's Course Funding Has Achieved
HDR UK provided scholarship funding to support the development of a series of master's programmes across the country. We spoke to two of the universities involved to find out how their courses have developed.
HDR UK is firmly committed to training the next generation of health data scientists – and ensuring that this country is a world-leader in the field. Part of this process has involved supporting the development of high quality master’s programmes.
Once firmly established it was hoped that each programme would develop to address a particular set of needs. The courses at the Universities of Cambridge and Leeds have both been highly successful and have each evolved in very different directions.
“ HDR UK funding was key to getting our health data science theme up and running and helping us develop this new course”
University of Cambridge
High quality master’s courses are essential to create a training pipeline to provide Britain with a world-class health data science workforce. HDR UK played a valuable role by providing support and funding scholarships to help get courses established. We asked the people behind the University of Cambridge MPhil in Population Health Sciences for an update on how their course is developing.
The MPhil course is now three years old and thriving – taking around 75 students a year from all round the world to study any of six themes.
These include around 15 specialising in health data science and the rest divided between epidemiology, public health, primary care research, global health, and infectious diseases.
Such has been its success that Dr Kalman Winston, Academic Director, says: “I would say it’s probably one of the most rigorous courses in this subject in the country.”
The Institute’s early support made an immense difference.
“HDR UK funding was key to getting our health data science theme up and running and helping us develop this new course which is a major evolution from our previous courses,” he added.
There are around 500 applicants a year, many are moving straight from undergraduate degrees but others – such as public health registrars – are already established in their careers and looking for advancement or a change of direction.
While entry qualifications are not prescriptive it’s necessary to have the equivalent of a 2:1 degree. Students wishing to specialise in health data science need to have a strong aptitude for maths and ideally some experience of studying it successfully at university level
Dr Winston says: “We want to get a good mixture of students, so if you’re from any background and you’ve got an interest in population health sciences and you’ve done some stats courses, it’s really worth applying.”
Dr William Astle, the Health Data Science theme coordinator and a University Senior Lecturer, said: “We are interested in identifying able students who can benefit from the course academically, those for whom a Master’s level training will open up future opportunities such as study for a PhD.”
The students themselves are one of the great strengths of the MPhil.
Dr Winston says: “There are a lot of amazing students who learn a lot from each other. One of our core values is the opportunity to mix and learn with people from all sorts of places and backgrounds.”
Another strength is that much of the teaching is by academics at the forefront of current research. There’s the added attraction that it is possibly the only place where health data science and population health sciences are combined in a single course.
Dr Astle says that the students attracted to the Health Data Science specialism have varied career ambitions. Many graduates of the course go into research, others find jobs in policy or work in government or for international bodies like the WHO. Others begin careers in the NHS or industry as informatics experts and statisticians.
There is also the distinction of having passed a highly rigorous postgraduate course at one of the world’s most academically intensive universities.
Dr Winston says: “We have a wide range of assessments. Students have to give presentations, produce a group essay, analyse a set of data and write a dissertation. It’s very hard, it’s a lot of work, but people come out with a lot of skills.”
Students, however, have the benefit of much closer supervision – both for their course work and their dissertations – than is provided by most universities.
Many applicants are currently from overseas and the course would welcome more applications from home students. A small number of scholarships are available each year to contribute towards the costs.
And the course itself never stands still.
Dr Winston says: “There’s a lot of emphasis on course development – it’s an evolution and I think that it’s continually getting even better.”
Master’s success led to PhD place
“The MPhil programme was instrumental in helping me connect with my current PhD supervisor, and it provided a strong foundation that has prepared me well for the demands of doctoral research. The course not only deepened my subject knowledge but also refined the research skills essential for success in a PhD programme. The variety of modules available in the course allowed me to gain skills in various areas of Biostatistics as well,” Juliette Limozin.
“ The NHS England staff tend to get some of the best marks. They're good - brilliant people.”
University of Leeds
The University of Leeds MRes in Data Science and Analytics has been a huge success since it was set up with HDR UK support. We spoke to academics and students about how it started and its evolution into a programme that is now focussed on transforming NHS England analysts into data scientists.
Since it was established in 2020 the MRes programme has carved out a distinctive and valuable niche in health data science postgraduate education.
Co-designed by the university, NHS Digital and HDR UK (which funded six scholarships), most of the 26 students have been professionals, based locally at the NHS England headquarters.
Owen Johnson, Associate Professor in the School of Computing, says that being close to the campus means “they just walk up the hill so we can do face-to-face teaching in a way that they probably wouldn’t get anywhere else”.
The course is having a significant impact on NHS England by tooling up its national data science and analytics team with new skills and experience.
Owen says: “We’ve evolved and this is now a course that’s very much geared towards NHS England professionals and on upgrading and speeding up how data research using NHS data is carried out. This brings enormous and direct practical benefits by improving how data research is carried out.
“That’s partly because once you’ve turned analysts into data scientists, it gets rid of a big bottleneck and a whole set of expenses for carrying out data research.”
Having a skilled central team of data scientists can do much to accelerate the work of external research organisations. It can remove the need for lengthy applications, and long waits, to get access to NHS data.
Owen says: “One of the biggest limiting factors to health data research is getting the data. That’s crippling a lot of health data research. In many cases it’s faster and simpler to do the research while the data remains in the secure environment.
“Having a strong central team that can do the research themselves tightens the cycle time. Also, if the team preparing the data extract understand the AI and health data research, they’re going to prepare data in a way that means it’s right first time.
“What I’ve seen too often is that after two or three months the research team realise the data extracts aren’t adequate because they’re missing things, or the quality is too poor or inconsistent. It’s expensive for everybody to do multiple issues of data.”
The university has a variety of data science and machine learning modules that students can choose from.
Owen says the NHS England students, who now need to have been working for a minimum of three years, normally shine.
“The NHS England staff tend to get some of the best marks. They’re good – brilliant people.”
During the first six months students learn how to write and research academically.
They are taught how to do literature reviews, critically compare different research methods and understand which are most appropriate in given circumstances.
One of the main features of the MRes is a large work-based project that lasts 18 months – as a result the course is now structured to be part-time over two years.
Owen says: “It elevates them. They’re not just doing something theoretical, they’re doing something in their own workplace.
“In that process they’re making the transition from being analysts to being data scientists.”
Case Study 1: Adam Hollings, an NHS Digital (now NHS England) funded student who works for NHS England.
I wanted to do the MRes as I had an interest in advanced analytical methods and theory and this seemed like a way to boost myself up in that area; I knew data scientists and was inspired by talks and seminars at work and wanted to try and become one too.
The course has had a profound impact on my career. It took my learning of statistics and analytical methods from a decade ago; then sharpened some elements and beat out the dints in other areas!
I was reforged with a new view on how data science and analytics should be done as well as how different techniques can be applied to achieve certain outcomes.
My final project, a critique and improvement piece of the Summary Hospital Level Mortality Indicator, was especially in-depth and technical. Just talking about the unfinished project during an interview for a Band 7 role helped me secure the position of Data Scientist (Data Wrangler) and the skills I learned on the MRes helped me to understand what researchers using NHS England data might want and need to do and help internal staff understand the importance of certain user requests.
The MRes took me from being an analyst and raised me to understand and be able to talk with other data scientists. Since then, I have been able to present at two HACA conferences on data science related work. The course also gave me renewed confidence after nearly a decade of teaching then a career shift back into analysis.
I’m very grateful to NHS England and Leeds University for the MRes and without it I might not have had the mindset and skills to be a data scientist – at the very least it would have taken a lot longer.
Case study 2: Christin Puthur, Oxford University data scientist.
I chose the MRes in Data Science and Analytics for Healthcare, funded by HDR UK, because it provided a unique opportunity to apply data-driven methods in the healthcare sector. The programme allowed me to work on a significant research project while building a strong foundation in key areas such as machine learning, AI, and causal inference.
Events organised by HDR UK, including a PPIE panel and a conference to showcase our project outcomes, provided valuable insights into health data science and networking with other professionals. Additionally, the HDR UK alumni network offered essential guidance on CV building, interview coaching, and job search strategies.
The MRes deepened my understanding of the complexities and sensitivities of working with healthcare data, and the high stakes of data-driven decision-making in the sector.
Collaborating with professionals from diverse fields such as pharmacy, medicine, and process mining during my research project further enriched my learning and broadened my approach to navigating the unique challenges of healthcare data.
This experience, particularly the research project, had a significant impact on my career, helping me secure a data scientist role at the department of population health of the University of Oxford. The MRes programme honed my ability to understand stakeholder needs, communicate data-driven findings effectively, and support decision-making through data science—skills that have been crucial in my career path.
