Role:  Research Assistant in Medical Image Analysis

Department:  School of Engineering

Grade: Research Grade 6 (£33,020 per annum)

Responsible to: Principal Investigator

Campus:  Belfast (Remote working within the UK may also be considered)

Fixed-Term for 5 months / Full-time

Due to the short-term nature of this post, the successful candidate must be available to commence immediately and will be required to hold proof of right to work in the UK at the time of application and for the duration of the post.

Job Purpose:

The postholder will contribute to the anatomical modelling of the trachea and oesophagus using a large dataset of CT scans. The role focuses on medical image processing and image segmentation to isolate these structures and the identify of key anatomical landmarks.  The postholder will develop predictive models to estimate key internal features based on simple clinical parameters such as height, gender, and age. Additionally, they will construct Statistical Shape Models to predict 3D morphological variations from these same clinical parameters.

The work supports a broader understanding of patient-specific anatomy, using machine learning techniques to capture population-wide variance. This position offers the opportunity to work with large-scale clinical data and develop expertise in medical image analysis.

Closing Date: 26th August 2026 at 23.30

Guidance regarding applications can be found here:  https://recruitment.ulster.ac.uk/information-for-applicants/what-to-expect-from-the-application-and-interview-process. If you are still having issues, please contact email: sj.mcfarlane@ulster.ac.uk stating the vacancy reference number.

Click on the links below for any relevant documents – Please note, these documents will not be available after the job advert closes. Please ensure that you download and save these.

Candidate Briefing Document - 043366

Please note: For remote working arrangements, the duties of this role must be carried out from within the UK, as the costs associated with employing staff to work outside the UK are prohibitive. Applicants must have the legal right to work in the UK.

Please be advised that due to the minimum salary thresholds imposed by the UKVI, this post will not qualify for university sponsorship under the Skilled Worker visa route. Please check your options here:  https://www.gov.uk/check-uk-visa

If you have any specific queries regarding eligibility to work in the UK, our Resourcing Compliance team may be able to help: Resourcing-compliance@ulster.ac.uk

We may create a 12-month waiting list for same or similar roles within the Department / Faculty.  The University reserves the right to extend the waiting list across the University if required for certain posts.

Ulster University recognises the potential benefits that Generative AI tools (for example Chat GPT) may bring to some candidates during the application process. In particular, we recognise the positive impact such tools may have with regard to equality, diversity and inclusion. When using AI, however, we encourage candidates to use the technology responsibly, ensuring that submitted applications provide an accurate representation of your skills, abilities and experience. Our selection activities are designed to robustly test and evaluate the extent to which candidates meet the selection criteria outlined for each role. This includes the use of interviews, presentations, written exercises and other additional selection activities as appropriate for each role.

The School of Engineering holds a Silver Athena SWAN Award in recognition of our commitment to advancing Gender equality in higher education. You can read more about what this means at https://www.advance-he.ac.uk/equality-charters/transformed-uk-athena-swan-charter and on our University website https://www.ulster.ac.uk/peopleandculture/employee-benefits/equality-diversity/athena-swan.

The University has a range of initiatives to support a family friendly working environment, including flexible working.