The appointment will be on UCL Grade 9.

We are seeking collaborative and self-motivated bioinformatician post-docs to work on evolutionary biology in lung cancer based around analysis of next generation sequence data from the TRACERx longitudinal lung cancer program. The successful applicant will have a proven track record of publications in high impact journals, be fluent in at least one of the following programming languages: C++, Python or R, and is expected to have strong skills in the field of one or more of the following: evolutionary biology, statistics, mathematics or machine learning. Prior experience with data analysis based on integrating large datasets is particularly desired.

Professor Charles Swanton is the lead investigator of the TRACERx initiative, a large scale longitudinal genomics study in lung cancer utilizing deep multi-region tumour sequencing. The focus of the project is the investigation of lung cancer evolution and the development of high throughput bioinformatics techniques to decipher cancer mutational signatures and tumour evolutionary trajectories through the disease course. The candidate will be expected to work within the TRACERx informatics team and utilise evolutionary, mathematical and statistical methods to deconvolute cancer evolution based in particular but not exclusively upon next generation sequencing data. In addition, the candidate will be expected to have multidisciplinary skills working with clinical and scientific staff and a desire to excel in the field of cancer evolutionary biology.

This post is funded for 5 years in the first instance.

The postholder will have a Postdoctoral qualification (PhD), experience in the field of evolutionary biology and previous experience of multi-disciplinary working. The postholder will have evidence of publications, excellent written and verbal communication skills and attention to details. He/she will also have good inter-personal skills with an ability to liaise effectively with other members of the group and the ability to present complex data at meetings.

UCL vacancy reference: 1720688.

Applicants should apply online. To access further details about the position and how to apply please click on the ‘Apply’ button below.

For any queries on the application process, please email: ctc.hr@ucl.ac.uk.

For enquiries about the post contact Sharon Vanloo, Operations Manager, Swanton Lab: (sharon.vanloo@crick.ac.uk).

No agencies please.

Closing date: 13th of May 2018.

Latest time for the submission of applications: 23:59.

Interview date: TBC.

We particularly welcome female applicants and those from an ethnic minority, as they are under-represented within UCL at this level.

Our department holds an Athena SWAN Silver award, in recognition of our commitment and demonstrable impact in advancing gender equality.