Senior Research Fellow (AI Adoption and Productivity)

We are seeking a motivated and collaborative individual to join our team as a Senior Research Fellow – AI Adoption and Productivity. The Productivity Institute (TPI) is seeking to appoint a Research Fellow to undertake analysis on the impact of this implementation on institutional productivity. The Research Fellow will support an independent academic evaluation covering three distinct user populations — professional services staff, academics and researchers, and students — and will help design the framework and baseline evidence that underpin a multi-year research programme on AI adoption at the University of Manchester.

You will be responsible for:

• Design and deliver mixed-method research on the adoption and impact of AI tools in a large complex organisation, under the guidance of the Principal Investigator.
• Conduct both qualitative and quantitative analysis.
• Develop articles, blog posts and executive summaries based on the literature reviews and relevant data analysis.
• Coordinate the data audit and the administration of baseline and follow-up surveys across staff and student populations, working with IT, HR and faculty contacts to assemble the necessary data.
• Support research-ethics, data-governance and information-security approvals required by the programme, and engage with internal University stakeholders (IT, HR, Teaching & Learning, faculties) and external partners.
  
  
  

We welcome candidates who bring diverse perspectives, experiences, and approaches to their work.

About You

We encourage applications from individuals with a wide range of backgrounds and experiences. You should demonstrate:

Essential Criteria:

• PhD degree or equivalent within a relevant subject area, e.g. economics, management, applied data sciences or innovation studies.
• Knowledge of, and interest in, the role of AI in digital transformation process, and the impact on economic and/or business performance.

Ability to combine qualitative and quantitative research techniques.

Experience of using programme evaluation methods.

Strong written and verbal communication skills and ability to convey technical material in non-technical terms for policy and other non- academic stakeholders.

Desirable Criteria:

• Experience designing and administering large-scale surveys, and working with linked administrative or telemetry data under GDPR.
• Familiarity with causal-inference methods for staggered programme adoption (for example, difference-in-differences with heterogeneous timing, event studies).
• Prior research on the economics of AI, digital tools, or technology adoption in organisations.
• Experience of qualitative case-study work alongside quantitative analysis.
  
  
  

We value transferable skills and real-world experience as much as formal qualifications.

Our benefits include:

• Generous employer contribution pension
• 29 days annual leave plus bank holidays, along with Christmas closure
• Ride to work and EV car scheme available
  
  
  

For more information, please see University of Manchester Benefits. You can also find information on our Flexible and Hybrid working here.

We are an open place of enquiry and challenge. We embrace and celebrate difference, diversity and debate, and we pride ourselves on being a place of education, learning and community where we are able, within the law, to question and test received wisdom, express new ideas and explore controversial or unpopular topics and opinions. Find out more from our Freedom of Speech Policy.

Enquiries About The Role, Shortlisting And Interviews

Name: Jun Du

Email Address: jun.du-3@manchester.ac.uk

General enquiries and administrative support

recruitmentservices.people@manchester.ac.uk

Technical and job portal support

https://jobseekersupport.jobtrain.co.uk/support/home

Applications close at midnight on the closing date.

Further particulars (with person specification) linked below.