Postgraduate research opportunities

Data Science for Studying Science, Innovation and Entrepreneurship

This scholarship welcomes applications that study management and policy aspects of science, innovation and entrepreneurship by employing advanced data science approaches and/or utilising new data sources.

Number of places

One funded place as well as a number of self-funded or externally funded places


Home fee, Stipend


17 June 2020


15 August 2020


42 months from October 2020


  • An excellent undergraduate degree with Honours (or overseas equivalent) in a relevant social science subject (business and management, economics, sociology or any other cognate discipline). We also welcome applicants with an engineering or science background, who demonstrate a strong interest in the topic. A Master’s degree (or equivalent) on a relevant subject is not essential but it would strengthen the application.
  • A strong interest or previous experience of studying science, innovation and entrepreneurship management or policy.
  • Prior knowledge and/or a strong willingness to learn advanced data science approaches (including but not limited to bibliometrics, patent analysis, advanced statistics, social network analysis, natural language processing and machine learning) as well as the ability to conduct research with mixed method approaches blending data science and qualitative methods.
  • Prior knowledge and/or a strong willingness to learn data science tools and frameworks (e.g. R or Python).
  • Excellent analytical and mathematical skills
  • A demonstrable aptitude to undertake research and develop into an independent researcher.
  • Excellent written and oral English language skills (see the application page for minimum test scores if English is not your first language).

Project Details

The scholarly study of science, innovation and entrepreneurship (SIE) is a crucial field in advancing the

understanding of SIE dynamics, providing evidence-based policy advice and guiding the practice. The field

has grown rapidly in recent decades with specialist top ranking journals and conferences, academic

departments and a vibrant community. Today the world faces complex issues such as ever-accelerating

technological change, increasingly skewed distribution of welfare gains from technologies and innovation,

intertwined sustainability and responsibility issues related to emerging technologies, and growing societal

grand challenges such as climate change, inequality and poverty. On the face of these challenges, the field

is still confined to the traditional boundaries of established disciplines such as economics and

management. In recent years, there have been multiple calls that the scholarly field of studying SIE is in a

crisis as the existing approaches have reached their “intrinsic limits” (Soete, 2019; Burmaoglu & Saritas,

2019; Martin, 2016; Martin, 2012).


One of the ways forward proposed to address these challenges is to embrace the recent advances in data

science, which is fundamentally affecting all scholarly fields across the board. Data science unlocks data

sources that were not previously conceived, equips scholars with the ability to replace traditional

simplistic models of the world with more nuanced approaches and enables rapid response to the

emerging phenomena. All these capabilities, in turn, provide opportunities to increase the rigour,

relevance and timeliness of such studies as well as their relevance of the existing debate and theoretical

frameworks. These opportunities are increasingly being recognised and captured by scholars in the field,

evidenced by large research programmes supported by research funders and increasing share of data science skills in researcher training in top universities.


We welcome applications that study management and policy aspects of science, innovation and entrepreneurship by employing advanced data science approaches and/or utilising new data sources. Applicants are required to put forward an outline research proposal that includes a clear research question and a relevant methodology. While the opportunity is open to any research proposal within this broad remit, we are particularly interested in proposals on the topics we have recently been working (science system transitions, social innovation, innovation policy, entrepreneurship policy).

Funding Details

  • UK/EU citizens/residents: Full fee waiver and annual stipend of circa £15,000 for 42 months.
  • Non-UK/EU citizens/residents: Fee waiver at UK/EU rate and annual stipend of circa £15,000 for 42 months. The remainder of fees (circa £11,000 per annum) should be financed by the candidate or an external sponsor.
  • We also welcome self funded or externally funded applications.


You will be registered to the PhD in Entrepreneurship programme based at Strathclyde Business School, under the supervision of Dr Abdullah Gök. You will be a part of Centre for Doctoral Training in Data Science for Studying Science, Innovation and Entrepreneurship.

Contact us

For any questions or informal enquiries, please contact Dr Abdullah Gök.

How to apply

At this stage, we are inviting applicants to apply for the scholarship only. The successful candidate will then be asked to complete an application for PhD study at Strathclyde.


All applications should include:


  • A cover letter indicating the candidate's relevant skills/experience and how these can contribute to this research
  • An outline research proposal on the broad topics mentioned in project details, including the problem statement, possible research questions, methodology and proposed academic and policy/practice contributions (min 2 pages).
  • An up-to-date CV
  • Relevant qualification transcripts (e.g. undergraduate and/or postgraduate degree)
  • Two references (please refer to guidance on references)
  • (Optional) English language test results (can be completed later)


Applications with missing documents will not be assessed.


When sending the above documents please use the following file-naming convention: fullname_typeofdocument


For example:


  • Johnsmith_coverletter
  • Johnsmith_CV
  • Johnsmith_proposal
  • Johnsmith_transcript1
  • Johnsmith_transcript2
  • Johnsmith_reference1
  • Johnsmith_reference2

Apply now by uploading your documents.