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AI Scientist (KTP Associate) - 24 months contract

The University of West London (UWL) is ranked as 41st in the UK in The Guardian University Guide 2026 and is the 1st London modern* university in The Times/The Sunday Times Good University Guide 2026. We are also the Number 1 London university for overall student satisfaction in the National Student Survey 2025**. The UWL community is a diverse body of students and staff who work together to create an environment of success and achievement. We celebrate the diversity of our staff and promote our values in practice through our commitment to inclusivity, progression, and success. 

* A modern university is a university established in 1992, or after. Excluding specialist providers. 

** Calculated as the average of all questions, using registered populations.

The School/ College/ Department 

The School of Computing and Engineering is a professional and student focused School with high quality teaching, student experience and research informed teaching at the top of its priority list. The School has strong links with local, national and international partners and enjoys state-of-the-art equipment and continues to invest heavily in its improvement. 

B4 Secure works as a trusted advisor to businesses and government departments, delivering a full range of intelligence services that not only address security challenges but also help clients navigate broader organisational risks.

The School of Computing and Engineering at the University of West London (UWL), in partnership with B4 Secure Limited, is seeking an AI Scientist (KTP Associate) to deliver an exciting new Innovate UK-funded Knowledge Transfer Partnership (KTP). 

The Role 

Working closely with the business partner supervisors at B4 Secure and supported by the UWL academic team, the KTP Associate will lead the design and implementation of an AI‑driven threat intelligence software system that automates OSINT threat monitoring and risk assessment. The project aims to transform the business partner’s business  workflows into an efficient, scalable, adaptive, and ethically aligned AI platform that enhances operational performance and supports sustainable business growth.

This role offers an outstanding career‑development opportunity to manage a high‑impact KTP project while being fully supported by an experienced team of academic and industry experts in AI, data science, cyber security, and ethical AI.

This post is fixed‑term for 24 months and primarily remote role; however, the successful candidate will be expected to attend in-person meetings in London for project collaboration and stakeholder engagement. Applicants should be located within a reasonable commuting distance to facilitate attendance when needed Reasonable travel expenses will be covered. 

The Person

The KTP Associate will be self‑organised, proactive, and comfortable prioritising work in a remote‑first setting, with the opportunity to drive real innovation in AI‑enabled threat intelligence. This interdisciplinary and technically advanced project requires a highly capable individual with strong theoretical grounding in Artificial Intelligence, computer science, or a related discipline. Prior industrial experience is not required.

For further information, applicants are encouraged to consult the Job Description, which provides detailed guidance on the role requirements and person specification.

In return, the Associate will receive the following benefits:

  • £2,000 personal training & development budget (in addition to salary) to support your professional growth and skills development
  • Regular engagement with the Innovate UK Knowledge Transfer Adviser and structured support from the KTP programme.
  • Multi‑disciplinary supervision and mentoring from UWL academics and the business partner.
  • Exposure to diverse stakeholders and real‑world users, including client pilots and demonstrations, providing commercial and product‑development experience.
  • Access to the expertise and resources of UWL and B4 Secure needed to deliver the project effectively, plus clear pathways to contribute to joint publications.

How to Apply 

To apply click on ‘Apply Online’ and fill out the application form. Further information about the application process can be found here: https://jobs.uwl.ac.uk/display.aspx?id=1253&pid=0 

Please email hr.recruitment@uwl.ac.uk  if you need any assistance with the application process.

Interviews are expected to be held in the week commencing 01 June 2026. 

For informal enquiries about the position please contact Julie Nel, CEO & Founder, B4 Secure, via email info@b4secure.co.uk or Professor Wei Jie, University of West London, via email wei.jie@uwl.ac.uk.

Additional Information 

Our department/school is under-represented in terms of staff from BAME (Black, Asian and minority ethnic) backgrounds, of LGBT+ identities, and with disabilities. UWL is committed to having a diverse and inclusive workforce, supports the gender equality Athena SWAN Charter, and is a Disability Confident Employer as well as a Diversity Champion for Stonewall, the leading LGBT+ rights organisation. We welcome applications from all sections of the community, particularly those mentioned above to increase diversity in our workforce.

Candidates must be able to demonstrate their eligibility to work in the UK in accordance with the Immigration, Asylum and Nationality Act 2006. 

A Standard DBS Certificate is required for this post (to be undertaken upon appointment) and candidates must be willing to undertake enhanced security screening and vetting checks.

We will intermittently review the applications as part of this open advert, therefore if successful, you will be shortlisted and contacted at any time. 

The University of West London reserves the right to close the role prior to this date should a suitable applicant be found.

Further Details:
Job Description
DBS

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Job Details
Department
School of Computing & Engineering
Location
On-Line
Salary
£40,834 per annum
Release Date
Wednesday 15 April 2026
Closing Date
Friday 15 May 2026
Interview Date
Friday 05 June 2026
Reference
COMP0092
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