The Liquid Biopsies and Cancer Diagnostics lab at the Cancer Research UK Cambridge Institute, University of Cambridge, pioneers new approaches for non-invasive molecular diagnostics using next-generation sequencing of circulating cell-free tumour DNA (ctDNA). Led by Dr Rosenfeld and a team of experienced translational genomics scientists, the lab establishes large collections of plasma and other samples from cancer patient across different clinical studies, and studies them using both genome-wide and targeted methods for sensitive detection of tumour-derived alterations. We develop high sensitivity analysis tools, and aim to progress these into clinical use by proof-of-concept translational studies to demonstrate their utility. We further explore the biophysical properties of ctDNA to study its origins and interactions and to inform the development of increasingly sensitive methods.
The lab and its collaborators have produced some of the key milestones in the liquid biopsy field using gene panels, exome sequencing, and shallow whole genome sequencing to detect, analyse and monitor ctDNA in plasma samples from hundreds of patients with different cancer types. The lab develops and uses a range of methods including hybrid-capture and amplicon-based sequencing, shallow and deep whole-genome sequencing, and methylation analysis, to profile samples from different bodily fluids from patients and model systems. The group is a dynamic mix of molecular biologists, bioinformaticians and clinical fellows providing a unique environment for development and learning in cancer genomics and translational research, with a strong focus on clinical application. The successful candidate will work closely with multiple members of the lab, and carry out exploratory analysis of various data-sets.
We are seeking to recruit an outstanding scientist with a PhD and extensive experience in bioinformatics or computational biology, and next generation sequencing data analysis in the field of cancer genomics. The successful candidate will play a key role in a large-scale project for earlier diagnosis of cancer, funded by generous grants from Cancer Research UK. The ideal candidate will have extensive experience of machine learning and data integration approaches for analysis of genomic sequencing and/or methylation data. Demonstrated experience in the development of statistical methods for robust and reproducible data analysis would be an advantage. You will be a highly motivated, detail-oriented individual with excellent communication skills and who is extremely organised. You will be able to work independently and interact well in a multi-disciplinary team environment.
Informal enquiries may be made to the Rosenfeld lab management team; firstname.lastname@example.org
Fixed-term: The funds for this post are available for 3 years in the first instance.
Once an offer of employment has been accepted, the successful candidate will be required to undergo a security check.
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Closing date: 1 March 2020.
Interview date: TBC
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