Research Associate in Computer Vision and Machine Learning

About us

The Centre for Machine Vision (CMV) is seeking to appoint a Research Associate to focus on applications of computer vision and machine learning.  This is a full time, fixed term post for two years.

The CMV is within the Department of Engineering, Design and Mathematics and is located within the Bristol Robotics Laboratory (BRL - https://www.bristolroboticslab.com/centre-for-machine-vision ), a joint venture between UWE and Bristol University.

The CMV is currently comprised of 15 researchers, five PhD students and four visiting academics and attracts funding from a range of bodies that include BBSRC, EPSRC and InnovateUK. We also undertake research funded by medical charities, as well as commercial consultancy work for various companies. The CMV specialises in real-world applications of computer vision and machine learning for the realisation of working prototypes and demonstrators, with a strong emphasis on data capture, modelling and analysis. Previous applications include agriculture (animal and plant monitoring), medicine (vision systems for patient diagnosis/analysis and human-computer interaction) and biometrics (human and animal face recognition and non-contact palmprint recognition). The work of the CMV team was graded to be of international standing in the 2021 REF, with 81% of CMV’s work was found to be world-leading/internationally excellent in terms of originality, significance and rigour.

About you

Candidates with experience of computer vision and/or machine learning are encouraged to apply. Successful applicants will have expertise in computer science or a related field, with a focus on computer vision or deep learning. A master’s level qualification, or equivalent, is essential; the candidate should be willing to register for a PhD in machine vision/machine learning.

In addition to a number of new projects starting or about to start, for example PIMS ID 10144655 (Support for Belron Projects) and PIMS ID 10487555 (IntelliPig), we have recently applied for funding in the form of major research projects related mainly to agri-tech and industrial automation applications. Example projects include: In-depth machine vision/deep learning analysis of pig images, for development of new methods for monitoring pig condition and health, and Innovative machine vision solutions for automotive camera/systems calibration.

We have recently received significant funding from NERC, for a water quality project focused on implementation of an agile sensing network for informing river health. We consider this to be a very timely and important project. It is likely that the appointed RA will work on this to develop an AI informed Water Quality Index, based on historical and live datasets, that can be visualised graphically, to enable users to understand how the quality of water is influenced by ‘discharge’ events, and to monitor how long the “signals” persist after these events. This will enable detection of water quality patterns that can be used to assist with decisions on water management (e.g. spill control/timing) for improving overall water quality control. There may also be opportunity for input on other projects, including human-computer interaction and healthy aging. These will depend on the progress on the existing projects and the priorities associated with this work.

Our projects focus on computer vision and machine learning applications that may include object detection and tracking, face analysis, data augmentation, object pose estimation, deep CNNs / reinforcement learning and GANs. 

You will also work closely with CMV colleagues to network with new external partners to develop new funded projects. Funding is available for making visits to the collaborating research groups and there will also be the opportunity to attend international conferences.

You will be expected to contribute to teaching, for example, introductory courses in machine vision and deep learning, and in the supervision of undergraduate and masters project students. 

Where is this role based?

This post is based at our lively Frenchay campus where we have invested in the latest facilities and resources to give both our staff and students access to everything they need to succeed.

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 Bristol , one of the UK’s most exciting and forward-thinking cities, we are regionally embedded and globally connected, with an established network of employer and academic partners.

We offer a wide range of employee benefits including progressive pay rates, 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 are proud to be part of a vibrant, multicultural city that celebrates diversity, we’re always looking for talented people from all backgrounds to join us. Our people are our strength, and diversity enhances our creativity and leads to better decision-making and problem-solving. Bring your talent and ambition to our growing community and find yourself in a stimulating and supportive environment where you’ll thrive.

We particularly encourage applications from Black, Asian, Multiple Heritage or Other Minority Ethnic candidates as we are currently under-represented in these areas within UWE Bristol, however all appointments are made strictly on individual merit.

As a Disability Confident employer, we welcome applications from those who identify as having a disability.

Further information

If you would like an informal discussion, please contact Prof Lyndon Smith on 0117 328 2009 or email: [email protected] .   

This is a fixed-term post for 2 years and is full-time working on a 1.00 FTE contract. This post is not available on a part time basis.

UWE Bristol is a campus-based University and it is vital to our success and the delivery of an outstanding experience for our students that our campuses are dynamic and vibrant places to learn and spend time. This role is therefore campus based with the opportunity to work from home on agreement with the line manager.

We may be able to sponsor qualifying candidates for this role under the Home Office Skilled Worker visa route. Please read our Skilled Worker Guidance to assess if you will be eligible to be sponsored under the criteria.

Please also refer to the Home Office Right to Work Checklist  which provides details of which documents are acceptable to prove your right to work in the UK. Should you be shortlisted you will be asked to produce your right to work documents at your interview.

You may also wish to explore other visa options which you are eligible for which will allow you to work in the UK.

Please note that UWE does not cover any visa or health surcharge costs.

Advice to applicants

We’d love to hear from you - if you are excited about joining us at UWE please complete our application form as soon as possible.

Tell us about how your skills and experience relate to the requirements of this role by describing how you meet each of the essential and desirable criteria listed in the Person Specification section of the Job Description, and include specific examples wherever possible.

Once we have completed shortlisting we will let you know the outcome of your application by email, so please check your inbox for updates.