Post-Doctoral Training Fellow - Bioinformatician

21/01/2019, 23:55

Sutton
Molecular Pathology
Computational Pathology & Integrated Genomics
Full time
Fixed Term
2 years
35
£30,715 - £36,433
The Institute of Cancer Research, London, is one of the world’s most influential cancer research institutes, with an outstanding record of achievement dating back more than 100 years. We provided the first convincing evidence that DNA damage is the basic cause of cancer, laying the foundation for the now universally accepted idea that cancer is a genetic disease. Today, The Institute of Cancer Research (ICR) leads the world at isolating cancer-related genes and discovering new targeted drugs for personalised cancer treatment.

Under the leadership of our Chief Executive, Professor Paul Workman FRS, the ICR is ranked as the UK’s leading academic research centre. Together with our partner The Royal Marsden, we are rated in the top four cancer centres globally.

The ICR is committed to attracting, developing and retaining the best minds in the world to join us in our mission – to make the discoveries that defeat cancer.

We seek a motivated postdoc to join the Computational Pathology and Integrative Genomics team led by Dr. Yinyin Yuan in a highly interdisciplinary project with Prof. Carlo Maley at Arizona State University, Dr Andrea Sottoriva at ICR and Prof Trevor Graham at Barts Cancer Institute. ICR were ranked first in the Times Higher Education league table of UK university research quality from the most recent Research Excellence Framework (REF 2014) for our high impact publications. We are world leaders in identifying cancer genes, discovering cancer drugs and developing precision radiotherapy. Together with our hospital partner The Royal Marsden, we are rated in the top four centres for cancer research and treatment worldwide. Our Cancer Research UK Cancer Therapeutics Unit is the largest academic cancer drug discovery and development group worldwide. We discover more new cancer drugs than any other academic centre in the world.

The Yuan lab at ICR develops pioneering deep learning approaches for the analysis of histopathological images and explores new ways to integrate image data with genomics (www.yuanlab.org). We specialise in the application of spatial statistics to harness rich spatial information in these images, which has been underused but provides crucial context for the understanding of the tumour microenvironment, and further, cancer evolution that could lead to treatment failure.  

The successful post holder will develop exciting new computational pipelines for integrating digital pathology data, generated from histopathology and cutting edge multiplex images from CODEX and/or CyTOF, with omics data in colorectal cancer. He/she will enjoy the highly collaborative environment at ICR and in this research program, and work closely with an international, highly recognised team consisting of biologists, clinicians, ecologists and computer scientists. He/she will have the opportunities to learn about latest cutting-edge biotechnologies/methods including deep learning, single-cell sequencing and high dimensional multiplexing, travel to conferences and partner institutes, excel in coordinating between programming and explore new research areas in medicine through collaborations.

Applicants must hold a PhD in Computer Science, Bioinformatics, Engineering, Ecology, Physics, Mathematics or Statistics. Knowledge/experience in medicine or deep learning is desirable but not essential.

Appointment will be on a Fixed Term Contract for 2 years, with a starting salary in the range of £30,715 to £36,433 p.a. inclusive, depending on experience. There is potential to progress on the salary scale up to £43,898 p.a. inclusive. The successful candidate will be based in Sutton, Surrey.

To apply, please upload your CV and complete an application form online

We consider all applications on merit and have a strong commitment to enhancing the diversity of our staff.
Additional Documentation for Candidates

This Program is closed to applications.