Research Assistant in Bioinformatics

University of Leeds
Leeds, United Kingdom
£27,924 to £33,309 p.a.
Closing date
Jul 1, 2022

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Science, Life Sciences, Cell and Molecular Biology, Pharmaceutical, Business Development
Full Time
Organization Type
University and College
Jobseeker Type
Academic (e.g. 'Lecturer')
Are you an early career researcher looking for your first challenge?

Do you have a background in bioinformatics?

Do you want to further your career in one of the UK's leading research intensive Universities?

The aim of this project is to create statistical and AI methods to predict early progression in patients with follicular lymphoma. Follicular lymphoma is a slow growing cancer and often patients require limited treatment for many years. A subset of patients however experience more rapid disease progression, and to identify them early is an important clinical problem. In this role you will analyse a large transcriptomic (RNA-seq) data set from patients and investigate its use to predict progression. You will collaborate with other researchers using digital pathology and genome sequence analysis to create more accurate methods based on data integration.

You should have a first degree/Masters in bioinformatics or a closely allied discipline, with experience in analysing RNA-seq or other high-throughput sequencing data.

The University of Leeds and the Faculty of Biological Sciences are committed to providing equal opportunities for all and offer a range of family friendly policies. The University is a charter member of Athena SWAN (the national body that promotes gender equality in higher education), and the Faculty of Biological Sciences was awarded a Silver award in 2020. We are proud to be an inclusive Faculty that values all staff, and are happy to consider job share applications and requests for flexible working arrangements from our employees. Our Athena SWAN webpage provides more information.

To explore the post further or for any queries you may have, please contact:

Professor David R Westhead, Professor of Bioinformatics


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