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Research Fellowship in Human AI-Teaming

The University of ManchesterManchester, United KingdomDeadline 30 Oct 2026
Location

Manchester, United Kingdom

Deadline

30 Oct 2026

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Overview

Institution
The University of Manchester
Location
Manchester, United Kingdom
Deadline
30 October 2026
Hours
Full Time (1 FTE) per week

About this position

Job Description

Applications are invited for a research fellowship focused upon how people and AI can and should work together in a collaborative partnership. The fellowship is jointly hosted by the University of Manchester, Manchester Metropolitan University and the University of Salford, and supported by the UK Government. The fellowship is initially through until March 2028, with the possibility of an extension.

Applicants are requested to submit a brief research proposal addressing the topic of human-AI collaboration with their application. If successful they will be required to revise this proposal, in consultation with colleagues from UK Government, both to address government priorities and to improve the fit of the proposal with the demands of the National Security context, where advances in AI capability could give significant efficiency gains but must be balanced against a strong regulatory regime.

Some of the research will assume a standard academic form and fellows will be expected to pursue publication in relevant academic journals, subject to approval from the government sponsor. Some may be classified and intended for use by UK Government and their partner organisations only. Fellows will therefore gain experience of two very different research environments and of negotiating the complexities of working between them.

The Fellow will have a base within one of the partner universities. They will have mentors both within their University and UK Government, to offer guidance and support. Mentors from the organisations will work together to ensure coherence and consistency in their advice and support. Fellows will be required to be in Manchester several days a week and so are expected either to be located in the North-West or willing to relocate.

Applicants should have completed or at least submitted a relevant PhD and have expertise in computer science, AI, machine learning and/or an intersection of those fields. This expertise should be explained in a letter of application and demonstrated in the abovementioned proposal, which short-listed candidates will be expected to present at interview.

The fellow must be eligible and willing to apply for national security clearance at a minimum level of Enhanced Security Clearance (eSC) and a preferred level of Enhanced Developed Vetting (eDV), making them subject to the provisions of the Official Secrets Act (which includes restrictions on travel to certain countries). UK nationals currently resident in the UK will normally be eligible, but all applicants should carefully consider their eligibility before applying for the fellowship. Information about vetting and clearance can be found on the UK Government Security Clearance website. The employer reserves the right to terminate a fellowship in the event of a loss of security clearance.

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

Email Address: bsfellowships@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.

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