AI and 3D Image Processing Engineer - KTP Associate

Post Title

AI and 3D Image Processing Engineer - KTP Associate

SBU/Department

School of Physics, Engineering & Computer Science

FTE

1.0FTE (working 40 hours per week)

Duration of Contract

Fixed term for 30 months

Salary

KTP Between £35,000pa and £40,000pa depending on skills and experience

Annual Leave

28 days per year, including bank holidays

Location

College Lane, Hatfield, and CrossTech, 11 Gough Square, London, EC4A 3DE

About the programme

This position forms part of the Knowledge Transfer Partnership (KTP) programme funded by Innovate UK (IUK). A KTP is a 3-way collaboration between a graduate (or post-graduate), a business and a university or research institution. KTPs are designed to deliver an innovation project and bring about lasting, transformative change. As a KTP Associate, you will lead the project with full support from company and academic supervisors, while benefiting from expert coaching and mentoring with one of IUK’s highly experienced Advisers.

The University of Hertfordshire wish to recruit a motivated, highly skilled & qualified graduate to lead and deliver a project with Cross Tech, pioneers in automated AI infrastructure inspection. This project will develop a real-time computer vision and edge AI system for intelligent rail monitoring, enabling early detection of hazards. The KTP includes access to management skills training delivered by Ashorne Hill, in addition to a £5000 training budget.

About Cross

Tech

CrossTech develops cutting-edge software designed to help the world move better. Their expertise in AI, Automation, Analytics, and Image Processing is helping railway systems in the UK, improve operational performance, efficiency, and safety.

Please visit

https://www.crosstech.co.uk/ for more information.

Main duties and responsibilities

The associate will develop an advanced real-time computer vision and edge AI system for intelligent rail monitoring and hazard detection. You will handle data collection and analysis and contribute to the design and organisation of the research project as well as contribute to academic peer reviewed papers and presentations. You will be expected to assist with the dissemination of results and outputs of the project and assist with collating and writing the final project reports and working papers. You will take an active part in the academic life of the school through participation in seminars and other events.

Skills and experience required

You will be proficient in Python (NumPy, PyTorch) and experienced with CNN/Transformer models and have experience working as part of a research team in a Higher Education Institution or in industry (e.g. final year project). You will have Strong foundations in AI/machine learning, particularly deep learning for video analytics and experience in managing real-world data capture and labelling from complex environments. You will have a methodical approach with attention to detail and problem-solving abilities, be able to plan and manage own activities effectively, as well as be the ability to deal with sensitive material with strict confidentiality. Exposure to intelligent transport systems (ITS), radar and AI for safety-critical applications is desirable as is an awareness of data governance, safety and security in operational environments.

Qualifications required

You will be educated with a minimum of a Degree or equivalent in Computer Science or a relevant discipline.

Please view the job description and person specification for a full list of the duties and essential criteria. Please attach a personal statement showing clearly how your skills and experience match the Person Specification.

Internal applicants – please ensure you apply via your employee self-service portal.

An appointment to this role may require an Academic Technology Approval Scheme (ATAS) certificate.

Due to the structure of KTP funding, appointees requiring a work visa will be able to commence employment only after confirmation of their having UK right to work that covers the entirety of the project. The visa position regarding sponsorship or support will be considered once the successful applicant has been determined. The successful applicant must also start in post by 19th December 2026 due to the KTP funding requirement.

Contact Details/Informal Enquiries

Lucy Cooper – lc24aau@herts.ac.uk

Closing Date

14 June 2026

Interview Date

TBC

Reference Number

REQ000612

Date advert placed

15 May 2026

We reserve the right to close this vacancy early if we receive a high volume of suitable applications.

Our vision is to transform lives and UH is committed to Equality, Diversity and Inclusion and building a diverse community. We welcome applications from suitably qualified and eligible candidates regardless of their protected characteristics and recognise there are different ways applicants may achieve the criteria in this document. We offer a range of employee benefits, discounted Sports Village memberships, and personal and professional development. #GoHerts

Proud member of the Disability Confident employer scheme

Disability Confident

About Disability Confident

A Disability Confident employer will generally offer an interview to any applicant that declares they have a disability and meets the minimum criteria for the job as defined by the employer. It is important to note that in certain recruitment situations such as high-volume, seasonal and high-peak times, the employer may wish to limit the overall numbers of interviews offered to both disabled people and non-disabled people. For more details please go to Disability Confident.