An exciting opportunity exists for 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.

This studentship is the result of an exciting new research collaboration between HDR UK and the University of Manchester Department of Computer Science.

It is also part of a UK-wide initiative involving the development of new analytical techniques, data linkage methods, and tools for data sharing while ensuring patient privacy and data security.

The PhD student will collaborate with, and be supported by, a team that is further developing HDR UK’s infrastructure for federated analytics.

They will be in a prime position to propose technological advances to be tested on real use cases, working with leading experts on healthcare data management and trusted research environments within the HDR UK network and the BioFAIR infrastructure.

The supervisors will be Carole Goble, Professor of Computer Science, and Stian Soiland-Reyes, Research Fellow, in the eScience Lab at The University of Manchester.

Project objectives

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

The studentship

  • A tax free stipend will be paid at the current UKRI rate of £18,622 plus tuition fees
  • This funding is available for home students
  • The student may be expected to participate in activities along with the other HDR UK PhD students.


Apply for the PhD

For further information and to apply for this PhD