Bioinformatics Research Fellow – Mammalian Gene Regulation
To study the evolution of genetic control of mammalian gene regulation. Closing on 1 Nov.
Grade 7 (£34,304-£40,927), 36 months
The mammalian genomics group at the Roslin Institute is looking for a Bioinformatics research fellow to join our team to study the evolution of genetic control of mammalian gene regulation. Using novel, genome-wide data on human and cattle regulatory variants obtained using the SuRE approach (https://www.nature.com/articles/s41588-019-0455-2), the research fellow will study where the impact of genetic variants is, or is not, conserved across mammalian species. By characterising the genomic features linked to the conservation of the impact of genetic variants on gene expression, the applicant will develop machine learning models for predicting the impacts of putative regulatory variants within and across species. As well as working on this unique and extensive dataset the researcher will benefit from being part of a wider group of bioinformaticians working on both human and livestock genomics (e.g. see recent papers: https://www.nature.com/articles/s41467-020-18550-1, https://www.nature.com/articles/s41467-019-13762-6). They will have the opportunity to be involved in international consortia and have access to substantial resources such as other unique mammalian datasets and the University of Edinburgh’s high performance computing infrastructure.
The position will be on grade 7 (salary as above) and is available initially for 36 months. Informal enquiries can be directed to Dr James Prendergast (email@example.com).
Please apply with your CV and a cover letter outlining your suitability for the role addressing the criteria set out in the skills section.
Your skills and attributes for success:
- Advanced degree (MSc/PhD) in a relevant quantitative discipline (e.g. Bioinformatics, Genetics/Genomics, Computational Biology or Data science)
- Experience with analysing “omics” data.
- Experience programming in a high-level scripting language (R or Python)
- Proficiency in Linux/Unix operating systems
- Experience of planning and executing research projects and complex integrative analysis of large datasets
- Experiencing with analysing RNA-seq data
- PhD in relevant discipline
- Machine learning experience in R or Python is desirable but not essential
All applicants are encouraged to apply online. The application process is quick and easy to follow, and you will receive email confirmation of safe receipt of your application. Applications should be received by the closing date of 1 November 2021.