Applications are invited for a postdoctoral computational biologist to join the Laboratory of Professor Sir Tom Blundell at the University of Cambridge, Department of Biochemistry, Central Cambridge.
The successful candidate will work on a project, funded by the Cystic Fibrosis Trust as a Strategic Research Centre in Cambridge, to understand the strain variation and development of antimicrobial resistance in Mycobacterium abscessus. This is a collaborative grant led by clinician Professor Andres Floto, and involving Professor Chris Abell,in Department of Chemistry, university of Cambridge, and Dr Julian Parkhill at the Wellcome Trust Genome Campus.
Mycobacterium Abscessus (Mab) is distantly related to tuberculosis, and can cause a devastating lung infection in CF individuals. This can be impossible to treat, often prevents safe transplantation, and leads to accelerated lung damage and death. The project will involve analysis of a sequenced global collection of over 1500 clinical isolates and a mutant library of Mab. The post-holder will make a computational protein-structure analysis of Mab proteome to identify critical genes responsible for survival and infection - these genes will then become targets for our Fragment-based Drug Discovery campaign.
The Blundell group has already begun to generate an Mab proteome database using modeling programs developed over the past 30 years, including Fugue, Modeller, and other software pipelines developed for the Mycobacterium tuberculosis database, CHOPIN. The post-holder will generate models built on structures of homologues, with multiple models for conformational states characteristic of different oligomeric states and ligand binding, including identification of hotspots and binding cavities, reflecting various functional states of the proteins. Knowledge of the computational proteome will provide crucial support for conventional and target-agnostic fragment-based drug discovery campaigns, and allow in silico chemical screening and cheminformatic predictions. The pipeline will also provide structural analyses of mutations, associated with strain variation and drug resistance, using our software SDM and mCSM. Detailed drug resistance/tolerance phenotyping of clinical isolates that have already been whole-genome sequenced will allow experimental validation of these predictions and provide a large training set for machine learning computational approaches. This will then provide the basis for analysis of new clinical isolates and the mutant library of Mab.
The successful candidate must have or be about to complete a PhD, preferably in a computationally focused research project. Knowledge of developing software in genomics and/or structural proteomics is required, with skills in coding in Python desirable.
Fixed-term: The funds for this post are available for 24 months in the first instance.
If you have any questions about this vacancy, please contact Prof Sir Tom Blundell (firstname.lastname@example.org).
To apply online for this vacancy, please click on the 'Apply' button below. This will route you to the University's Web Recruitment System, where you will need to register an account (if you have not already) and log in before completing the online application form.
If you have any questions about the application process, please contact Adriana Dote (email@example.com).
Please quote reference PH13944 on your application and in any correspondence about this vacancy.
The University values diversity and is committed to equality of opportunity.
The University has a responsibility to ensure that all employees are eligible to live and work in the UK.