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Renal, pancreatic, and colorectal cancers are responsible for approximately one fifth of the estimated 2.7 million new cancer cases and a quarter of the 1.26 million cancer deaths in the European Union in 2020. Further, incidence rates of these cancers are rising among young adults. Despite improvements in cancer diagnosis and treatment, survival rates have not substantially improved for these three cancers. The blood proteome, along with whole genome sequencing in the blood and tumours, and high-quality epidemiological data likely hold importance insights valuable for cancer prevention and prognosis.

RESEARCH EXPERIENCE, RESEARCH METHODS AND TRAINING

The selected individual will acquire computational skills completing statistical analyses including machine learning, whole genome sequence, and Mendelian randomisation analyses. This will include developing skills in Python/R and in bash using high performance computing. In completing this project, the individual will work with a team of international collaborators as part of the DISCERN consortium to advance our understanding of the causes and drivers of prognosis for renal, colorectal, and pancreatic cancers. This includes processing data from WGS technology, Olink and Somalogic data, and other data including spatial proteomics and model organoids, as well as large prospective cohort questionnaires. By the end of this DPhil, individuals will be a competent genomic epidemiologist.

FIELD WORK, SECONDMENTS, INDUSTRY PLACEMENTS AND TRAINING

Individuals will receive computational training and will be expected to present results at national/international conferences/meetings. 

PROSPECTIVE  STUDENT

The ideal candidate will have a Masters degree in a relevant area (e.g. statistics/epidemiology/computer sciences/bioinformatics) but most importantly, the individual must have a resilience to solving complex problems and the ability to embrace the unknown and find working solutions.  

 

Supervisors