KTP Associate Digital Technology Lead - AI & Computer Vision
| Dyddiad hysbysebu: | 27 Mai 2026 |
|---|---|
| Cyflog: | £40,000 i £45,000 bob blwyddyn |
| Oriau: | Llawn Amser |
| Dyddiad cau: | 14 Mehefin 2026 |
| Lleoliad: | Evesham, Worcestershire |
| Gweithio o bell: | Hybrid - gweithio o bell hyd at 2 ddiwrnod yr wythnos |
| Cwmni: | University West of England |
| Math o swydd: | Cytundeb |
| Cyfeirnod swydd: | R09386 |
Crynodeb
This is an exciting opportunity to work in a collaborative partnership between the University of the West of England (UWE Bristol) and Foster + Freeman Ltd under the UK Government sponsored Knowledge Transfer Partnership (KTP) programme. This is a 24-month fixed-term role offering comprehensive development opportunities, including residential management and business training through the national KTP programme at Ashorne Hill, plus a £2,000 annual training budget for tailored personal development.
You’ll be based at our award‑winning partner, Foster + Freeman, in Evesham, Worcestershire. With over 40 years’ experience, the company designs and manufactures leading forensic technology for police, forensic scientists, and government bodies, and continues to innovate with cutting‑edge, AI‑driven forensic systems. Supported by academics from UWE Bristol’s Centre for Machine Vision, you will help enable Foster + Freeman to develop new and novel AI models/systems to ease usability of sophisticated technical instruments used for real-time detection/identification of materials of interest at crime scenes.
UWE Bristol and Foster + Freeman celebrate diversity and seek talented people from all backgrounds to join us.
About you
PhD in Artificial Intelligence, Computer Vision, Machine Learning, or a closely related discipline.
Experience designing, training, and validating machine learning models, including object detection and video segmentation.
Experience working with imaging hardware to collect data and create annotated machine learning datasets.
Proficiency in Python and common AI frameworks (e.g. PyTorch, TensorFlow).
Strong problem-solving skills, with ability to adapt methods to real-world conditions.
Where you will be working
You will be based at Foster + Freeman, Evesham, Worcestershire.
Why UWE Bristol?
We are one of the largest providers of Higher Education in the South West with 38,000 students and 4,000 staff from right across the globe. Based in vibrant Bristol, our ambitions are to make a positive difference to our planet, transforming futures through actions and solving real world challenges.
We offer a wide range of employee benefits including progressive pay rates, very generous annual leave and career average pension schemes as well as retail savings, onsite nursery and opportunities for training and personal development.
Add your individuality to ours
UWE Bristol recognises the power of a truly diverse university community.
We’re part of a vibrant, multicultural city and welcome talented people from all backgrounds. Diversity is our strength, enhancing creativity, decision‑making, and problem‑solving. Join our supportive community and thrive.
We particularly encourage applications from global majority candidates as we are currently under-represented in this area, however all appointments are made strictly on individual merit.
As a Disability Confident employer, we encourage applications from disabled or neurodivergent candidates.
Further information
If you would like to speak to us to find out more about this role, please contact Wenhao Zhang email: Wenhao.Zhang@uwe.ac.uk
This is a full-time, fixed-term post for 24 months, working 37.5 hours per week.
You’ll be based at our award‑winning partner, Foster + Freeman, in Evesham, Worcestershire. With over 40 years’ experience, the company designs and manufactures leading forensic technology for police, forensic scientists, and government bodies, and continues to innovate with cutting‑edge, AI‑driven forensic systems. Supported by academics from UWE Bristol’s Centre for Machine Vision, you will help enable Foster + Freeman to develop new and novel AI models/systems to ease usability of sophisticated technical instruments used for real-time detection/identification of materials of interest at crime scenes.
UWE Bristol and Foster + Freeman celebrate diversity and seek talented people from all backgrounds to join us.
About you
PhD in Artificial Intelligence, Computer Vision, Machine Learning, or a closely related discipline.
Experience designing, training, and validating machine learning models, including object detection and video segmentation.
Experience working with imaging hardware to collect data and create annotated machine learning datasets.
Proficiency in Python and common AI frameworks (e.g. PyTorch, TensorFlow).
Strong problem-solving skills, with ability to adapt methods to real-world conditions.
Where you will be working
You will be based at Foster + Freeman, Evesham, Worcestershire.
Why UWE Bristol?
We are one of the largest providers of Higher Education in the South West with 38,000 students and 4,000 staff from right across the globe. Based in vibrant Bristol, our ambitions are to make a positive difference to our planet, transforming futures through actions and solving real world challenges.
We offer a wide range of employee benefits including progressive pay rates, very generous annual leave and career average pension schemes as well as retail savings, onsite nursery and opportunities for training and personal development.
Add your individuality to ours
UWE Bristol recognises the power of a truly diverse university community.
We’re part of a vibrant, multicultural city and welcome talented people from all backgrounds. Diversity is our strength, enhancing creativity, decision‑making, and problem‑solving. Join our supportive community and thrive.
We particularly encourage applications from global majority candidates as we are currently under-represented in this area, however all appointments are made strictly on individual merit.
As a Disability Confident employer, we encourage applications from disabled or neurodivergent candidates.
Further information
If you would like to speak to us to find out more about this role, please contact Wenhao Zhang email: Wenhao.Zhang@uwe.ac.uk
This is a full-time, fixed-term post for 24 months, working 37.5 hours per week.
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