Application closing date: 11/09/2023
Salary: \xc2\xa337,099 per annum
Job category/type: Research
The School of Medicine, Dentistry & Biomedical Sciences (MDBS) at Queen\'s University Belfast, is currently seeking to appoint an exceptional candidate to the post of Research Fellow to work as part a new CRUK-funded Early Detection project within the colorectal cancer (CRC) Molecular Pathology Research Group (www.dunne-lab.com).
In collaboration with our international partners, this project aims to utilise a dataset that include digital histology and transcriptomics data to uncover the molecular signalling that underpins early dissemination in CRC. Overall, this project aims to unveil the interplay between the epithelial tumour and surrounding immune/stromal cells to ultimately improve our understanding of CRC.
The highly motivated and ambitious candidate will become an integral member of a dynamic, collaborative and well-equipped research group that puts a strong focus on interdisciplinary data-driven research. Our group provides a stimulating research environment where collaboration and development of new ideas is strongly encouraged, alongside support for career development for emerging talents. The overarching goals of this research group are to develop a greater understanding of disease to improve survival rates for patients with CRC, through precise dissection of the transcriptional signalling pathways underpinning histological features of cellular invasion and metastasis.
Our group is primarily focussed on biological discovery, identification of molecular signalling and/or morphological phenotypes that will enable improved understanding of disease and translation of potential therapeutic options. This approach involves a combination of molecular biology, computational analysis and pathological assessment, enabling an integrated evaluation of multiple layers of molecular information.
The post-holder will work within an established interdisciplinary team and will be required to have a strong understanding of the biology underpinning signalling cascades in cancer that emerge from data analysis, and how these relate to key pathological features in CRC. The successful candidate will utilise the unique data from our human tissue samples and mouse tumour models to develop new, and refine existing, molecular subtypes in CRC through a combination of translational bioinformatics and digital pathology.
The successful candidate must have, and your application should clearly demonstrate you have:
Times Higher Education
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