14524 - Postdoctoral Research Fellow in Computational Biology
| Company: | The University of Edinburgh |
|---|---|
| Salary: | £41,064 - £48,822 |
| Hours: | Full-time |
| Location: | Edinburgh, EH16 4UU |
| Working pattern: | On-site |
| Job type: | Temporary |
| Posting date: | 20 Jul 2026 |
| Closing date: | 3 Aug 2026 |
Summary
Grade UE07: £41,064 - £48,822 per annum
School of Regeneration and Repair / Centre for Inflammation Research
Full-time: 35 hours per week
Fixed-term: 7 months
Together we can do great things. Be part of something bigger.
Join the University of Edinburgh and you’ll be making a difference to everything around you. Be part of something bigger – where you’ll do meaningful work, grow and progress, be rewarded and recognised, and benefit from our strong commitment to your wellbeing. There are so many reasons to join us.
The University of Edinburgh is a world-class organisation. We look for the best in the field across all disciplines and provide a working environment where academics can develop their careers and passion for their chosen subject area. We offer the full range of academic roles and have a genuine focus on our students’ performance and wellbeing.
The Opportunity:
We are looking for an enthusiastic and motivated postdoctoral research fellow in bioinformatics, to work on a project using cutting-edge single-cell and spatial transcriptomic approaches to understand the cellular and molecular mechanisms regulating liver fibrosis and to identify novel therapeutic targets for liver disease.
The successful candidate will work with Professor Prakash Ramachandran within the Centre for Inflammation Research at the University of Edinburgh. This 7-month post is funded by an MRC Senior Clinical Fellowship award to Professor Ramachandran. The post-holder will analyse single-cell and spatial transcriptomic data from human liver samples, to dissect cellular, molecular and spatial changes in the fibrotic liver. We anticipate that the combination of these approaches will identify novel approaches to selectively modulate pathogenic cell types as an antifibrotic therapy for patients with liver disease.
Your skills and attributes for success:
• Expertise in relevant computational approaches including analysis of single-cell and single-nucleus RNA-seq data
• An understanding of liver disease and/or fibrosis pathobiology
• An ability to work with wet lab scientists to design strategies to validate key findings from computational work
• Critical appraisal and analytical skills for interpreting qualitative and quantitative information
• Good verbal and written communication skills
• Self-motivation, initiative and ability to work both independently and as part of a team
This post is full-time (35 hours per week); however, we are open to considering flexible working patterns. We are also open to considering requests for hybrid working (on a non-contractual basis) that combines a mix of remote and regular on-campus working
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