Machine Learning Research Scientist in Video Movement (KTP Associate)

Post Title: Machine Learning Research Scientist in Video Movement (KTP Associate)

SBU/Department: School of Physics, Engineering and Computer Science

FTE: 1 (working 37.5 hours per week)

Duration of Contract: Fixed term for 35 months

Salary: Between £35,000pa to £42,000pa depending on skills and experience

Annual Leave: 20 days per year plus Bank Holidays

Location: College Lane, Hatfield, and Transpharmation Ltd, a virtual company with a base at London Bioscience Innovation Centre, so the role will be mainly working from home

About the programme: This position forms part of the Knowledge Transfer Partnership programme (KTP) funded by Innovate UK (IUK). A KTP is a 3-way collaboration between a graduate (or post-graduate), a business (or not for profit organisation) 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 dynamic, highly skilled & qualified graduate to lead and deliver a project with Transpharmation Ltd, a neuroscience focused Contract Research Organisation (CRO). This project will develop an innovative software tool that tracks behavioural and motor function changes, by analysing human facial expressions, utilising advanced machine learning techniques.

About Transpharmation Ltd: Founded in the UK in 2010, Transpharmation is a scientist-led contract research organisation (CRO) specialising in neuroscience. Transpharmation connects drug developers with cutting-edge technology platforms to accelerate the discovery of life-changing medicines.

• You will be required to develop state-of-the-art facial expression recognition techniques while addressing their limitations in accurately detecting expressions in clinical populations.
• This entails a deep and thorough understanding of the available data, data sources, collection methods and the scale impacting how data is treated.
• Identifying and using suitable AI methods (e.g. Deep Neural Network) and rule-based methods (Human Intelligence) for this specific task is essential and technically challenging.
• You will also be expected to develop prototypes for individual development stages, alongside GUI development and rigorous testing.
• This will include fully documenting the programme code and creating detailed system dataflow diagrams while adhering to tight commercial timelines.

You will handle data collection and analysis and contribute on the design and organisation of the project as well as work with academic team members on peer reviewed papers and presentations. You will be expected to disseminate the results and outputs of the project and ensure the collating and writing of the final project reports are of a high standard. You will take an active part in the academic life of the School through participation in seminars and other similar events.

• Expertise of Machine Learning and programming skills are essential, Knowledge of software development and understanding of deep neural networks are also desirable.
• You will be methodical, have good attention to detail and problem-solving abilities, as well as be able to handle sensitive data with strict confidence.
• This role requires you to have knowledge of appropriate databases for the discipline and be able to conduct literature searches in the discipline using appropriate electronic resources, with an interest in applying technology in different forms.
• You will need good written communication, interpersonal and presentation skills in English, supported by a strong work ethic and self-motivation, whilst working effectively in a team setting.

You will have a minimum of a degree (or higher degree) in Computer Science or a closely related 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.

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 be available to start work by 18 May 2026 due to the KTP funding requirement.

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

Contact Details/Informal Enquiries: Deborah Tebbutt, Accounts & Operations Manager,

Closing Date: 23 October 2025

Interview Date: To be confirmed

Reference Number: REQ000308

Date advert placed: 02 October 2025

The University of Hertfordshire is committed to promoting equality of opportunity and valuing diversity. We are a Disability Confident Employer and an Athena SWAN member institution.