| Location: | Glasgow |
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| Salary: | £37,694 to £46,049 per annum |
| Hours: | Full Time |
| Contract Type: | Fixed-Term/Contract |
| Placed On: | 19th October 2026 |
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| Closes: | 9th November 2026 |
| Job Ref: | 856539 |
As a Research Associate, under the general guidance of Professor Kim Kavanagh, you will develop prediction models for head and neck cancer, as prt of the NIHR funded project EVEREST-HN, whist working collaboratively with the broader EVEREST-HN team. Alongside the predictive modelling research, the associate will be required to create accurate documentation, following the guidance of external consultants, which will be essential for the incorporation of the model into software as a medical device - a key deliverable of EVERESTHN. You will write up research work for publication, in collaboration with colleagues, and disseminate the results via peer reviewed journal publications and there may be opportunity to present at conferences.
To be considered for the role, you will be educated to a minimum of PhD level in an appropriate discipline, or have significant relevant experience in addition to a relevant degree. You will have sufficient breadth or depth of knowledge in statistics and building and evaluating predictive models and a developing ability to conduct individual research work and to disseminate results. You will have an ability to plan and organise your own workload effectively and an ability to work within a team environment. You will have excellent interpersonal and communication skills, with the ability to listen, engage and persuade, and to present complex information in an accessible way to a range of audiences.
Whilst a Post-Doctoral Research Associate is ideally sought for this position; applications from candidates who are close to PhD completion or whose award is pending, are welcome. In such circumstances, the appointment will be made at Research Assistant level (grade 6) and duties will be adjusted to reflect the grade of the post. This will continue until the PhD award is confirmed, at which point the duties and grade will be revised accordingly.
Applicants may use tools such as AI to support their application; however, all submissions must accurately reflect their own experience and understanding. The University reserves the right to verify the authenticity of application materials and may reject applications where concerns arise.
Initial interviews have been scheduled for Wednesday 18th November 2026.
For informal enquiries, please contact Professor Kim Kavanagh at kim.kavanagh@strath.ac.uk
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