Tired of viruses and fruit flies? Want to work on something really important for a change? Come and help us to figure out cancer evolution!
We are looking for outstanding candidates to work on inferring patterns of tumor evolution from genomics data. We work with a close group of clinical collaborators, both locally and internationally, who will provide multi-sample bulk sequencing and single-cell data sets. We plan to adapt methods from population genetics and phylogenetics to the cancer setting. Key questions will be to compare mutation rates and selection hotspots between the genomes of cancer clones.
This position is ideal for somebody trained in evolutionary biology in model systems to make the transition to biomedical applications in cancer.
The successful applicant will have a PhD in a quantitative field like mathematics, statistics, physics, engineering, bioinformatics, or computer science. A background in evolutionary biology, molecular evolution or population genetics is highly desired. The applicant should have a good biological background and excellent computing skills. The atmosphere at CI is very collaborative and interactive; good communication skills are key.
To apply, please visit http://www.jobs.cam.ac.uk/job/12614/
- Beerenwinkel et al (2014) Cancer evolution: mathematical models and computational inference, Systematic Biology.
- Ross and Markowetz (2016), OncoNEM: Inferring tumour evolution from single-cell sequencing data, Genome Biology, 17:69
- Schwarz et al (2015), Spatial and temporal heterogeneity in high-grade serous ovarian cancer: a phylogenetic reconstruction, PLoS Med, 12(2)
- Yuan et al (2015), BitPhylogeny: A probabilistic framework for reconstructing intra-tumor phylogenies, Genome Biology, 16:36