In the time it takes you to read this sentence, your body will have finished producing about 5 million new cells; each of these cells had to accurately copy, or replicate, the six billion bases of DNA in their genome exactly once. DNA replication stress is characterised by the frequent slowing and stalling of replication forks, which can result in the chromosomal breaks and rearrangements that lead to genome instability, and ultimately to cancer. Replication stress can be induced by oncogenes, leading to the hypothesis that oncogene-induced replication stress is an early driver of cancer. Viruses such as human papillomavirus (HPV) bring viral oncogenes into the cells they infect, and this research will use the unique model of HPV-infected human skin cells as a model system to uncover the precise steps from oncogene-induced replication stress, to genome instability, to cancer initiation.
The successful candidate will use cutting-edge bioinformatics and artificial intelligence methods to study the spatial patterning and consequences of DNA replication stress and mitotic defects induced by oncogenes. You will be a vital part of a multi-institution, cross-disciplinary team that includes Dr. Sarah McClelland (Barts Cancer Institute) and Dr. Eva Petermann and Professor Jo Parish (University of Birmingham). You will have access to the world-class high-performance computing facility at the University of Cambridge and be embedded in a team of physicists, engineers, and mathematicians working side-by-side with wet lab scientists in the Cambridge Department of Pathology. You will be supported by the vibrant and growing computational biology community within the Department of Pathology and will synergise with the DNA replication and genome stability communities within the University of Cambridge.
Informal enquiries and requests for further information are very welcome and should be addressed to Dr Michael Boemo: firstname.lastname@example.org
Further information on the Boemo Lab is available at: www.boemogroup.org
Applicants should have completed, or be close to completing, a PhD in a quantitative field (such as physics, computer science, mathematics, engineering) or in the life sciences with demonstrable computational experience (such as bioinformatics or computational biology). Applicants should feel comfortable working in at least one programming language and should be able to work both independently and as part of a multidisciplinary team.
University of Cambridge website: www.jobs.cam.ac.uk/job/38717/