Wellcome Trust PhD Programme in Science

The availability, scale and depth of data collected in the course of health care, by or about patients – combined with data-driven approaches to its analysis – is creating a paradigm shift in health care and its delivery. Machine learning and other automated methods of analysis will only succeed in providing useful insights for health and care if we understand health data in practice: how data is actually generated, interpreted and used.

Human-centred data science operates ‘at the intersection of human-computer interaction, computer-supported cooperative work, human computation, and statistical and computational techniques of data science’ while preserving ‘the richness associated with traditional methods while utilising the power of large data sets’ and encouraging critical social perspectives on health data in practice. We adapt this concept to the 'health data in practice' doctoral training programme with the goal of developing highly skilled future leaders able to apply interdisciplinary perspectives to research and innovations in health data science for the benefit of patients, the public, health care systems and society.

Our east London location

Barts and The London is committed to pioneering medical education and research. Being firmly embedded within our east London community, and with an approach to education and research that is driven by the specific health needs of our diverse population, the programme will draw on these networks to enhance your research.

Programme management team 

Professor Carol Dezateux Programme Director; Professor of Clinical Epidemiology and Health Data Science; Associate Director, Health Data Research UK; ‘Actionable Information’ Theme Leader
Professor Sandra Eldridge Professor of Biostatistics, Director of Pragmatic Clinical Trials Unit; ‘Effective and Efficient Evaluation’ Theme Leader
Professor Patrick Healey Professor of Human Interaction; ‘Human-Data Interaction’ Theme Leader
Professor Deborah Swinglehurst Professor of Primary Care, Director of Postgraduate Studies; ‘Health Data in Practice’ Theme Leader
Dr Eleanor Groves [Interim] Programme Manager

For queries regarding the programme please contact hdip-dtp@qmul.ac.uk.

Year 1: MRes in Health Data in Practice

The MRes programme will provide:

• an introduction to key concepts and research methods and analysis highlighting relevant methodological issues and challenges that comprise the interdisciplinary foundations of the programme and will include an introduction to research design, qualitative and quantitative methods, and societal and ethical issues related to data technologies
• experience of possible research areas for further study including opportunities to apply the knowledge gained and undertake a small research project during the MRes year
• an environment in which you can develop a solid understanding of the wider context of health data and critical thinking in this field. 

The programme comprises:

• Three compulsory taught modules (worth 75 credits in total)
• Three optional taught modules (worth 15 credits each)
• One project module (worth 60 credits) 

Total – 180 credits: Level 7

See full breakdown of modules

Years 2-4: PhD

The programme is framed in four scientific themes: Human-data interaction; Health data in practice; Effective and efficient evaluation; and Actionable information. You will work with your supervisors to develop an interdisciplinary research proposal within one of these four themes.

See more information on the themes

You are expected to pass the six- to nine-month progression via a 2,000-word report and a short 10-minute oral presentation to a Progression Panel comprising supervisor(s), relevant Director of Graduate Studies and the Programme Director or Co-Directors.

There are further milestones at 18 months (20,000 word report to the same assessors), and again at 30 months (to include additional data since the 18 month report plus a plan of the thesis).

Transfer to write-up status in the final year is considered a progression point and submission of the thesis within four years is a requirement.

You will also be supported to submit at least one manuscript and to present at relevant national/international scientific meetings during your studentship.

Each student will have a clear supervision plan with regular supervisions. The Director will meet with you on an annual basis to reflect on your year and get feedback on your progression, and will operate an open door policy at other times of the year if additional support is needed.

You will be supervised by at least two research active supervisors from different disciplines who will work with you to develop an interdisciplinary research proposal within one of four themes:

• Human-data interaction
• Health data in practice
• Effective and efficient evaluation
• Actionable information

Learn more about the themes

If appropriate, the supervisory team will include a member from a partner organisation (NHS, industry).

The programme brings together internationally-leading scientists with strong track records in research and PhD supervisions spanning biological, clinical, population, computer, and social sciences, as well as the arts and humanities, including digital humanities and bioethics. It harnesses the breadth and depth of expertise at our internationally leading research-intensive university, and our membership of the Health Data Research (HDR) UK and Alan Turing Institutes, building on our strong local partnerships with health professionals, patients and the public in seldom-heard disadvantaged populations receiving health care in real world settings.

Potential supervisors

Our training programme will introduce you to a wide context for your science and enable your development as ‘human-centred’ health data scientists capable of drawing on diverse concepts and disciplines and of engaging with real-world settings. Our programme leverages the strong track record of Queen Mary in developing and sustaining an innovative, inclusive and empowering research culture for its students and staff.

Our Researcher Development unit provides a comprehensive spectrum of courses and a range of support for PhD students including language training, presentation, critical appraisal, reading and writing skills, leadership, inner coaching, and resilience, time and project management, public engagement and communication skills. You will be expected to complete at least 210 hours of training and development during the course of the PhD, with a minimum required in each of the following four UKRI domains*: Knowledge and intellectual abilities, Personal Effectiveness, Research Governance and Organisation, and Engagement, Influence and Impact. You will also be offered transferable skills training which is reviewed at supervisions when objectives are set.

Every PhD student has a personal tutor who is independent of their academic supervisors, and who monitors their academic progress and provides pastoral care when needed.

*UKRI domains:

Our vision is to create a vibrant and inclusive interdisciplinary learning environment, which signals the importance we attach to diversity and inclusivity in our interactions, and which provide a safe and welcoming environment in which individuals can flourish and create. Our vision is aligned with that of the Wellcome Trust's Reimagining Research group, which aims to create a research culture that: 

• supports creativity, with ambitious and collaborative working across disciplines and institutions 
• prioritises diversity and inclusion, so that everyone benefits from supportive relationships no matter what their background
• produces open research, which is conducted with honesty and integrity.

Research environment

You will access science in internationally-leading centres, at the forefront of the science and execution of pragmatic clinical trials, and innovative evaluation of complex interventions and social practice in health care, incorporating ethnographic approaches. It includes leading computer scientists researching human interactions and decision-making, and the development and communication of trustworthy and explainable algorithms, as well as research groups from psychology, digital humanities, bioethics, linguistics and drama applied to health, with whom they interact. It will be closely integrated with the work of the Institute for Advanced Data Science, and Centres for Intelligent Sensing and Advanced Robotics at Queen Mary. Our leadership in the Discovery Programme – an innovative near real-time integrated health record for 2.2 million people – presents an unprecedented and trusted opportunity to access this important and unique asset to understand health data in practice.

NHS

The following NHS organisations will provide access to internships and placements, access to clinicians, patients and commissioners, and channels for dissemination and public engagement:

• Barts Health NHS Trust
• Primary Care Networks and general practices linked to the Clinical Effectiveness Group
• Public Health departments and clinical commissioning groups in Tower Hamlets, City & Hackney, and Newham
• The Discovery Programme: data publishers and stakeholders

Industry

The following organisations will provide access to industry placements for students and potential research collaborations:

• MedCity
• Learning Health Solutions

Other UK research organisations

HDRUK and The Alan Turing Institute: opportunities for internships, placements and exchange visits including leveraging this site’s international links in Canada and Australia and their role as Welsh Administrative Data Research UK hub.

You will be supported in your career transition through individualised, coherent career management support with access to mobility opportunities, mentoring, enterprise support and internships, as well as embedding integrated placements and internships within the training pathways.

At the end of the third year, you will meet with the Programme Director and your supervisor to discuss career transitions and develop a plan for placements, training and skills development. You will also have the opportunity to apply to the Programme Transition Fund.

The School provides support for work and industry placements for doctoral students reaching the end of their PhD and transitioning into new roles. As well as working closely with the NHS, we have access to industry partners through MedCity’s Collaborate to Innovate programme. Students can access an eight-week QIncubator programme and QConsult – QMUL’s award-winning employability programme.

Careers and Enterprise at Queen Mary

Queen Mary has two careers consultants dedicated to supporting PhD students, which together with a wide range of events, including PhD alumni discussion panels, speed networking events, and employer-led discussions, can help you to go on to a wide range of careers within academia and beyond.

While conducting your projects, you will receive advice, training and support around project management and presentation skills from the Queen Mary Careers and Enterprise team which also offers a range of support to prepare students for job applications, interviews, work experience, and career choices.

Queen Mary also provides support for PhD students and women researchers from all backgrounds, ages and stages of their lives through the Springboard Women’s Development Programme.

Eligibility information and details of resources the studentships provide (including stipend) can be found of the Wellcome website.

You must be a graduate or student who has, or expects to obtain, at least an upper second-class degree (or equivalent for EU and overseas candidates) in a relevant subject, which includes (but not confined to) statistics; computer sciences; mathematics; bioinformatics; psychology; biomedical sciences as well as qualitative disciplines including (but not confined to) anthropology; sociology; science and technology studies; and organisation studies.

Candidates with other relevant qualifications or research experience may also be eligible. Please contact us if you would like to discuss your eligibility.

Successful candidates will display their passion for a career in research, good communication skills and scientific knowledge of the field.