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Research Studentship in Knowledge Engineering

Research Studentship in the Future of Open Data

Shaping a modern approach to open data from a World-leading science facility

4-year DPhil studentship 

Supervisors: Professor Susanna-Assunta Sansone and Dr Philippe Rocca-Serra, Data Readiness Group (, Department of Engineering Science, University of Oxford; Professor Steve Collins, Diamond Light Source Ltd.


Did you know that at Diamond Light Source alone - the UK’s national synchrotron facility – more than 10PB of research data is generated every year on topics ranging from cancer treatment, battery materials, arts & heritage restoration, and food science? Do you want to play a key role in increasing the potential of this data to benefit society, creating world-class solutions for 21st Century problems?

Diamond is in the process of transforming its relationship with the vast quantity of research data produced in partnership with thousands of researchers. Our goal is tobetter address key societal challenges by ensuring that research data are openly available to all humans and machines in a way that enhances the value of the scientific research. Diamond has teamed up with experts from the University of Oxford who are among the prime-movers in a developing new paradigm in data management, based on FAIR (Findable, Accessible, Interoperable, Reusable: principles. The project is aimed at understanding opportunities and barriers in moving towards FAIR and open data in a wide range of science disciplines, from energy materials and palaeontology to studies of viruses and drugs.

The successful candidate will have an opportunity to shape the project, depending on their skills and interests.

This exciting collaboration between Oxford University and Diamond sets out to understand the implications of adopting FAIR Principles and the effects of its implementation on synchrotron data. The DPhil project will examine the current data structure, the types of research questions being asked, the evolving landscape of metadata standards, semantic web technologies, and the latest technologies for data representation and discovery.

The student will spend time (50/50) in Professor Sansone’s group at Oxford, and in Professor Collins’ team at Diamond, where they will learn about the latest advancement in the FAIR data ecosystem, and synchrotron science, respectively. Professor Tony Hey, Chief Data Scientist at STFC, will serve as Advisor.

This DPhil project may address the following illustrative questions:

● What are the cultural barriers to open science and FAIR data?

● What are the most promising technologies for data discovery?

● What form of query service would be appropriate to answer the kind of questions that future data consumers will be asking?

We welcome applications from students who may have alternative ideas about research questions to drive forward our open science programme.

Using specific use cases and scenarios, one or more potential FAIR-enabling frameworks will be demonstrated, along with a FAIRness maturity model to guide process improvement.

This DPhil project is designed to deliver novel conceptual and methodological contributions to enhance the value of Diamond’s research data to society.Specifically, it will define and prototype how to move from current manually-focused operations to a streamlined, unambiguous and AI-ready framework.

This DPhil project will also guide future Diamond data management policy towards achieving goals of better data for better science, where scientific evidence is routinely available in a transparent, trustworthy and persistent manner to drive science forwards.



The studentship is open to Home classified students only. Full details of the EPSRC eligibility requirements:

Award Value

Course fees are covered at the level set for the UK student (c. £8620 p.a. in 2022-23). The stipend is at least £18,062 per annum.

Candidate Requirements

We are searching for somebody with excellent academic potential and a commitment to researching and developing a new paradigm in open science. A first-class degree in science or computer science is desirable, but we will consider students from other backgrounds.

An ideal candidate would have experience of data science, some familiarity with social science research methods, as well as high degree of independence, excellent communication skills, and fluency in English. We will provide training in areas in which you may not be familiar, along with first-hand experience of collecting and processing data at Diamond.

Application Procedure

Informal enquiries are encouraged and should be addressed to Professor Susanna-Assunta Sansone (


Candidates must submit a graduate application form and are expected to meet the graduate admissions criteria.  Details are available on the course page of the University website.

Please quote 23ENGIN_SS in all correspondence and in your graduate application.

Application deadline: noon on 7 April 2023 

Start date: October 2023