英国比特森癌症研究所2021年招聘博士后职位（肿瘤生物学）

Postdoctoral Research Scientist - Prof. John Le Quesne

Cancer Research UK

Job description

Deep Phenotyping of Translational Dysregulation in Tumour Tissues

Would you like to develop your scientific career in a research institute that is founded on the quality of its people, acknowledged for its collaborative environment and designed to promote the development of the most outstanding and dedicated scientists? Many early career researchers have already made that decision and at present over 100 of them are now benefiting from our excellent training programme.

The Cancer Research UK Beatson Institute supports cutting edge research into the molecular mechanisms of cancer development and is one of the leading research institutes in Europe. The Institute provides an outstanding research environment, underpinned by state-of-the-art core services and advanced technologies, with special emphasis on imaging, metabolomics, and in vivomodels.

Our innovative and ambitious research themes focus on understanding the regulation of the tumour microenvironment and cancer metabolism, in particular:

Intrinsic cancer cell vulnerabilities caused by cell growth

Interplay between the tumour microenvironment, metastasis and recurrence

Biology of early disease, aimed at developing a ‘Precision Prevention' approach

The Le Quesne laboratory has a world-class track record in tissue-based studies of solid malignancy, and combines large tumour cohorts, classical histopathology methods, quantitative digital pathology, deep phenotyping techniques (e.g. multiplex imaging of tissue sections, machine learning methods), and molecular methods in the study of tumour biology.

We currently have a vacancy for a biologist/computational biologist who will work on a CRUK programme investigating the roles of translation dysregulation in intact tumour tissues. Specifically, we and our co-Investigators are elucidating how the control of helicase activity in mRNA translation is altered and co-opted by tumour cells, and how this influences hallmark phenotypes such as immune evasion, microenvironment composition, signalling and proliferation, at single-cell and tissue organisational levels.

Our group uses state-of-the-art methods in tissue staining (Polaris/Codex multiplex platforms) and digital pathology to generate multidimensional datasets encoding cellular locations and single-cell levels of gene expression in sections of animal and human tumour tissues. Spatial transcriptomic methods and facilities are also established and available (GeoMX). We have established pipelines for staining and data extraction, and are constantly developing and improving the methods applied. We have access to exceptional cohorts of human and mouse tumour tissues, and collaborate closely with basic science, mouse modelling, and computational science groups.

The successful applicant will largely be concerned with the extraction of biological meaning from multiplex stained images and spatial transcriptomic datasets, using a range of algorithmic approaches (classical digital image analysis, AI methods) in commercial software (Halo/Visiopharm/Inform), and subsequent analyses of these data (classical statistical methods, spatial methods such as ecological analysis and/or topological data analysis, machine learning). A collaborative approach will be essential in order to make maximum use of the information available.

Essential:

A PhD in a relevant field

Motivated by biological curiosity

Proven track record in forming and testing hypotheses from large datasets

Familiarity with tumour histology and good knowledge of basic tumour biology

Experience with digital pathology methods and quantitative pathology

Statistical ability (eg survival analysis, clustering methods, pathway analysis)

At least a good theoretical understanding of machine learning methods as applied to tissue images

Desirable:

Specialised knowledge of regulation of gene expression and mRNA translation

Specialised knowledge of the tumour microenvironment

Experience in multiplex image analysis and/or highly multidimensional datasets

To find out more about this unique opportunity to establish advanced skills and expertise in the exciting field of quantitative cancer biology in intact tissues, please contact Prof John Le Quesne at j.lequesne@beatson.gla.ac.uk for more details.

Closing date for applications: 7 th of March 2021

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