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Old 10-15-2019, 07:37 AM   #1
Location: UK

Join Date: Feb 2009
Posts: 31
Default Cancer Data Scientist @ UEA, Norwich, UK

Applications are invited for the post of Senior Research Associate in Bioinformatics to undertake a leading role in the Prostate Cancer Research Centre “Comprehensive characterisation of prostate cancer subtypes to inform precision medicine” project, under the supervision of Dr Daniel Brewer.

In this project we will build on our existing machine-learning approaches to integrate all clinical and ‘omic data from the PanProstate Cancer Group ( to identify prostate cancer subtypes and use these to improve our understanding of the phenotypes of advanced disease. You will lead the UEA part of this project and perform analyses, in particular you will be identifying novel subtypes from the PanProstate Cancer Group dataset, characterising those subtypes, cataloguing other clinically-relevant subtypes and determining status in samples, and will begin the translation of subtypes for clinical use.

The research will be based in the Cancer Genetics team at the Norwich Medical School, which is an interdisciplinary team comprising a mixture of bioinformaticians and lab-based scientists. We have a broad interest in translational cancer based molecular studies with the aim of improving patient care. The Cancer Genetics lab plays a central role in the International Cancer Genome Consortium (ICGC) Prostate UK group and played a pivotal role in setting up the Pan-Prostate Cancer Group a collaboration between all the major prostate cancer sequencing projects in the world.

You will have a PhD degree or equivalent experience in computer science or a relevant numeric biological subject, (e.g. bioinformatics, computational biology), strong organisational skills and a good track record in publications. You should also have experience in performing machine-learning techniques and of managing a project with large amounts of data, together with well-developed analytical, practical, and programming skills. An enthusiasm for working in an interdisciplinary environment and the ability to interact and communicate effectively with scientists from other disciplines including clinicians, scientific computing IT, and biologists is also essential.

Acceptable first degree: Computer Science, Physics, Mathematics, Engineering, Biological Sciences, Biochemistry, Biomedical Science.

Closing date: 4th November 2019.

Further particulars and an application form can be obtained from:
danielsbrewer is offline   Reply With Quote

data science, genomics, machine learning, prostate cancer

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