We are seeking a motivated post-doctoral scientist to join the newly established Systems Cancer Pathology group at the CRUK Cambridge Institute headed by academic pathologist Dr Raza Ali. Understanding how tumours coevolve with the tissue microenvironment (TME) is a pre-requisite for the effective use of immunotherapy, and may determine which pre-cursor lesions progress and which do not.
The successful candidate will lead the analysis of a unique multidimensional tissue imaging (imaging mass cytometry) dataset to investigate emergent features of the TME as it transitions from normality through pre-cursor in situ disease to established invasive breast cancer. We have assembled a unique resource coupling meticulous paired tissue sampling of precursor and invasive disease for multidimensional imaging to multiplatform genomic data across thousands of samples from over two hundred patients. Quantification of up to fifty proteins at subcellular spatial resolution will enable in-depth mapping of key cell phenotypes, their interactions and relational features (‘micro-niches’) that define TME dynamics through disease progression. Having precisely defined TME states, we will use genomic data to ask how these changes are determined by driver alterations and whether they exert a reciprocal effect on tumour evolution. This work will characterise TME transitions during cancer progression with unparalleled depth. It has the potential to identify the tissue phenotypes that define tumour evolution and determine the probability of disease progression.
This is a one-of-a-kind opportunity to join a newly established lab working in one of the most exciting areas of cancer research within a leading institute. Frequent interactions with scientists from a range of disciplines (pathologists, oncologists, genomics, multiplexed imaging, astronomy etc.) will be essential for the success of this work. The role will provide extensive experience of deploying imaging mass cytometry (already successfully deployed within the institute) with quantitative analysis to answer questions with biological and clinical relevance. There will be ample opportunity for methods development and pursuit of independent research arcs. The role is best suited to candidates with training in computational biology, however outstanding individuals with some experience of computational biology but lacking formal training are also encouraged to apply. Candidates will have completed or be near completing a doctorate in a relevant quantitative discipline, computational biology or pure biology with a quantitative element. Scientists with a passion for high dimensional single cell analysis of human tissues will flourish in this role.
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 basic disclosure (criminal records check) check and a security check.
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The closing date for applications is 31 January 2021. The interview date is TBC.
Please quote reference SW22596 on your application and in any correspondence about this vacancy.
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