Research Assistant, Natural & Computing Sciences
Listed on 2026-03-14
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Business
Data Scientist
Research Assistant, Natural & Computing Sciences (NCS
256R)
School/Section Natural & Computing Sciences Division Unspecified Staff Category Research Position Type Part Time Grade Grade 5 Salary £33,002 per annum, pro rate, actual rate £6,600.40 per annum NCS
256R Closing Date 24-MAR-2026 Documents
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This post will be based within the School of Natural and Computing Sciences at the University of Aberdeen. The School has strong expertise in computer science, data science, and artificial intelligence, with a growing emphasis on interdisciplinary and applied research.
Job DescriptionThe Research Assistant will support the EX-AIM project (Enhancing Anatomy Learning with Explainable AI–Enabled Misconception Detection), an interdisciplinary educational research initiative applying explainable artificial intelligence to medical education. The role will involve close collaboration with educators from the School of Medicine, Medical Sciences and Nutrition, particularly in digital assessment design and feedback for applied anatomy education.
Salary will be at the appropriate point on the Grade 5, £33,002 per annum pro rata for 0.2 FTE actual rate of pay £6,600.40 per annum and negotiable with placement according to qualifications and experience.
This post does not meet the minimum requirements for visa sponsorship under the Skilled Worker Route. We are therefore unable to consider applicants for this post that require sponsorship to work in the UK.
The closing date for the receipt of applications is 24 March 2026
The School of Natural and Computing Sciences embraces a diverse working environment and recognises the many benefits this can bring. Applications from individuals from across all of the equality protected characteristics are encouraged.
Please NoteIf you are unable to complete an application online, please contact the Recruitment Team ( ) to make alternative arrangements for submitting your application within plenty of time before the advertised post closes.
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