Research Fellow

Are you an ambitious computational biology researcher looking for your next challenge? Do you have a background in analysing data from both isolated and in situ single cancer cells? Do you want to further your career in one of the UK’s leading research intensive Universities?

The University of Leeds is one of the top 75 universities in the world. We have a truly global community, with more than 39,000 students from 170 different countries and over 9,000 staff of 100 different nationalities. Established in 1904, we have a strong tradition of academic excellence, reflected in first-class student education, along with world-leading research that has a real impact around the globe.We are seeking an enthusiastic and highly motivated individual to assist in analysis of single cell multi-omic and single cell spatial data, to develop or apply cutting edge approaches and integrate these datasets to yield biological and clinical insights about brain cancer treatment resistance.You will have a PhD or equivalent research experience in bioinformatics or computational biology, and a strong track record in the analysis of single cell datasets from human tumours, as evidenced by peer-reviewed publications in this field. Importantly, you will have a strong desire to translate single cell data into real biological meaning for patient impact.

What We Offer In Return

• 26 days holiday plus approx.16 Bank Holidays/days that the University is closed by custom (including Christmas) – That’s 42 days a year!
• Generous pension scheme plus life assurance– the University contributes 14.5% of salary
• Health and Wellbeing: Discounted staff membership options at The Edge, our state-of-the-art Campus gym, with a pool, sauna, climbing wall, cycle circuit, and sports halls.
• Personal Development: Access to courses run by our Organisational Development & Professional Learning team.
• Access to on-site childcare, shopping discounts and travel schemes are also available.
  

And much more!If you are looking for a role that will enable you to autonomously tackle longitudinal single cell multi-omics and spatial datasets to wring out as much information on treatment resistance mechanisms and therapeutic vulnerabilities as possible, to include the development of new methods and tolls as required, apply today.

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

Dr Lucy Stead, Associate Professor and Head of Glioma GenomicsEmail: l.f.stead@leeds.ac.uk