Professional Doctorate Data Science

The first industrial doctorate of its kind will equip you with interdisciplinary research and practical skills for a job in data science or data analytics.

Key facts

  • Award PhD
  • Start date September 2021, January 2022, September 2022, January 2023
  • Duration Doctorate full-time: 36 months, Doctorate part-time: 72 months
  • Mode of study Part-time, Full-time, Campus based, Stand-alone modules

Our Professional Doctorate in Data Science is the first industrial doctorate of its kind, and is supported by The Data Lab innovation centre.

We build on Stirling’s highly successful taught MSc Data Science to equip you with a range of cutting-edge, interdisciplinary research and practical skills and tools, that will lead to an academic or industry job in the area of Data Science, with possible applications to sectors including, e.g., life-sciences, finance, engineering, computing, healthcare, fintech, business.

In addition to enhancing students’ employability through work-based learning, the doctorate prepares you to undertake interdisciplinary Data Science research, jointly supervised by world-leading Stirling academics and Data Science industry experts.

The Professional Doctorate consists of a one-year taught programme, based on Stirling MSc programmes in Data Science, and a two-year research programme, to be conducted in collaboration with an industrial partner around industry-relevant research questions. Students could be employees of the industrial partner looking for further training and qualification, or have already established a (potential) collaboration with an industrial partner willing to support the project.

Each of our MSc in Data Science or in Fintech may offer the opportunity to establish a suitable collaboration with an industrial partner, and then grant access to the second year of the Professional Doctorate in Data Science on a research programme agreed with the industrial partner.

Specific projects and collaborations can be considered on a case-by-case basis.

Top reasons to study with us

Course objectives

This professional/industrial doctorate is designed to:

  • Equip professionals with the required multi-disciplinary skills, and underlying theoretical, practical and transferable knowledge, to undertake practitioner-oriented, impact-led research in data science
  • Give sound training in relevant practical, investigative, analytical and generic skills required for research in the area of data science
  • Experience of data science challenges and applications in a wide range of areas, such as business, healthcare, life science, fintech and scientific disciplines
  • Provide the opportunity to plan, undertake and prepare publication quality research

Work placements

The research component of the Professional Doctorate in Data Science is a project of industrial interest to be carried out in collaboration with a company supporting the project.

Flexible learning

If you’re interested in studying a module from this course, the Postgraduate Certificate or the Postgraduate Diploma then please email Graduate Admissions to discuss your course of study.

Faculty facilities

The Professional Doctorate can be attended both as a full time or part-time course. The taugh component is organised around learning material provided online, contact teaching and tutorial hours, and an “open-door” approach allowing students a direct contact with lecturers, providing for great flexibility in the organisation of study. The research component consists of a research project whose development can be planned by agreement between the student, the company and the academic supervisor.

If you’re interested in studying a module from this course, the Postgraduate Certificate or the Postgraduate Diploma then please email Graduate Admissions to discuss your course of study.

Changes at Stirling

Find out about important changes including how you'll be taught, start dates and how we're making campus safer.

Which course would you like to apply for?

Professional Doctorate Data Science

Search for another course