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Department of Computer Science

Sharing reproducible analyses in Big Healthcare Data Infrastructures

Primary supervisor

Additional supervisors

  • Stian Soiland-reyes

Additional information

Contact admissions office


  • Directly Funded Project (UK Students Only)

This research project has funding attached. It is only available to UK citizens or those who have been resident in the UK for a period of 3 years or more. Some projects, which are funded by charities or by the universities themselves may have more stringent restrictions.

Project description

An exciting new research collaboration between Health Data Research UK and the University of Manchester is funding a UK PhD studentship within the Department of Computer Science.

Health Data Research UK (HDR UK) is a national institute dedicated to improving health outcomes and advancing medical research through the use of data. Established in 2018, HDR UK is a partnership between leading universities, research institutions, and the National Health Service (NHS) in the UK. The primary mission of HDR UK is to harness the power of health data to drive scientific discoveries, develop innovative treatments and interventions, and ultimately improve patient care. By integrating and analysing vast amounts of health data, including electronic health records, genomic data, and other relevant information, HDR UK aims to generate insights that can transform healthcare delivery, policy, and research.

The University of Manchester, the University of Nottingham and the University of Dundee have established a collaborative network to explore innovative ways to use health data for research and healthcare improvement. These initiatives involve developing new analytical techniques, data linkage methods, and tools for data sharing while ensuring patient privacy and data security. This funded PhD is an opportunity for training and collaboration with a wide network of researchers within those institutions.

In particular, at the University of Manchester, we want to better understand the challenges of computational reproducibility and FAIR data sharing within HDR UK federated data infrastructures, especially focussing on technology potential, limitations, integrity measures and handling of sensitive data.

We are looking to recruit a PhD student with an interest in developing and applying emerging approaches for federated computational analytics (e.g. scientific workflow systems) and metadata management across distributed systems.

You will be collaborating with and be supported by our team that concurrently is further developing HDR UK's infrastructure for federated analytics, and will be in a prime position to propose technological advances to be tested on real use cases, working with UK's leading experts of healthcare data management and trusted research environments within the HDR UK network and the newly established BioFAIR infrastructure for UK life science researchers.

Project objectives:

The project will aim to meet the following objectives. These are broadly outlined below, and will be finalised and made more specific during the PhD.

1) Systematic review exploring existing literature on workflow management systems and methods to capture federated provenance and structured metadata
2) Systematic review limitations, opportunities, ethical and privacy concerns that restricts FAIR sharing of sensitive healthcare data, identifying potential countermeasures
3) Prototyping of a system that can filter federated workflow provenance to make it publishable as open datasets
4) Development of framework for open sharing of provenance for sensitive data analysis
5) Development of metadata models for mapping sensitive data identifiers

Further Information:
You will work with Carole Goble (Professor of Computer Science) and Stian Soiland-Reyes (Research Fellow) in the eScience Lab at The University of Manchester; they both have a long track record of international research and development of scientific workflow systems, provenance standards and FAIR data sharing practices across life sciences.

You may be expected to participate in some HDR UK activities along with the other PhD studentship recipients.

This funding is available for UK home students, at the current UKRI rate (tax free stipend of 18,622 GBP and tuition fees), and runs for up to 48 months. International students who don't meet the UKRI Home student residency requirements may also apply, but may have to top up for International tuition fees.

Applicants should hold a 2:1 undergraduate degree or better, and a masters degree in Computer Science or a subject relevant to one of data science, information modelling, Web technologies, Linked Data, knowledge graphs, or health care data processing; or equivalent international qualifications.

For informal enquiries in relation to this project, please email Stian Soiland-Reyes using the address below.

Applications for this studentship should consist of a full detailed CV and a covering letter outlining relevant experience and interest in the PhD area. A statement of your suggested approaches to answering the PhD brief should also be included in the covering letter.

Apply using the University of Manchester's Postgraduate Admissions system and select "Postgraduate by Research" and "PhD Computer Science (48) - Full-time". Note that the admission system portal in periods may experience heavy load.

Deadline for applications: 18th September 2023

Carole Goble (, Stian Soiland-Reyes ( use subject "HDR QQ2"

Person specification

For information


Applicants will be required to evidence the following skills and qualifications.

  • You must be capable of performing at a very high level.
  • You must have a self-driven interest in uncovering and solving unknown problems and be able to work hard and creatively without constant supervision.


Applicants will be required to evidence the following skills and qualifications.

  • You will have good time management.
  • You will possess determination (which is often more important than qualifications) although you'll need a good amount of both.


Applicants will be required to address the following.

  • Comment on your transcript/predicted degree marks, outlining both strong and weak points.
  • Discuss your final year Undergraduate project work - and if appropriate your MSc project work.
  • How well does your previous study prepare you for undertaking Postgraduate Research?
  • Why do you believe you are suitable for doing Postgraduate Research?