|Salary:||£36,770 to £44,388 UCL Grade 7, per annum, inclusive of London Allowance.|
|Placed On:||25th May 2022|
|Closes:||23rd July 2022|
Full Time, Fixed Term
We are seeking a collaborative and self-motivated computational cancer genomics post-doc to work on metastatic evolution and migrations using novel single-cell whole-genome DNA sequencing (scWGS) data.
The CRUK-funded project will focus on the design and development of computational methods and algorithms to analyse metastatic evolution and migrations using newly generated scWGS data. The unique combination of cutting-edge revolutionary scWGS technologies with the TRACERx/PEACE availability of longitudinal extensive metastatic tissue sampling (>40 samples per patient), clinical annotations, and orthogonal multiomics datasets makes this project an unprecedented opportunity to investigate complex metastatic processes and to demonstrate the importance of formal consolidated computational methodologies. Full details of the project are available at: https://t.co/3RuniFk5kv. For further information and informal enquiries, please contact Dr Simone Zaccaria (firstname.lastname@example.org).
The successful candidate will be based within the Computational Cancer Genomics research group (https://www.ucl.ac.uk/cancer/zaccaria-lab) at the UCL Cancer Institute (https://www.ucl.ac.uk/cancer). The research will be conducted at both the UCL Cancer Institute and the Francis Crick Institute in close collaboration with the renowned and established multi-disciplinary team of computational biologists, cancer evolutionary biologists, and lung cancer translational researchers within the TRACERx and PEACE studies.
The post is funded for 3 years in the first instance with a start date after 1st September 2022 and with the possibility of extension for another 2 years.
The successful applicant should have a related PhD (or equivalent experience) and a proven track record in cancer computational biology, have previous experience with NGS data analysis, be fluent in the Python programming language, and is expected to have strong skills in the field of genomics and desirably one or more of the following: cancer and evolutionary biology, statistics, algorithmics, and mathematics. Prior experience in the development of algorithms to identify genomic variants from DNA sequencing data and investigate their evolution is particularly desired.
Applicants should apply online. To access further details about the position and how to apply please click on the ‘Apply’ button above.
For enquiries regarding the application process please contact Cancer Institute HR Office email@example.com.
Latest time for the submission of applications: 23:59.
We particularly welcome applications from black and minority ethnic candidates 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.
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