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Senior Research Associate in Bioinformatics
Ref: RA1724
£33,797 to £40,322 per annum
The post is offered on a full-time, fixed term basis from 1 March 2020 to 31 August 2023.
We are seeking a highly-motivated senior post-doctoral bioinformatician/data scientist with expertise in machine learning and data integration to take a leading role in an exciting new project "Comprehensive characterisation of prostate cancer subtypes to inform precision medicine” funded by a Prostate Cancer Research Centre grant. This project will expand on previous work where we used our existing machine learning approaches to identify novel prostate cancer subtypes that were informative of clinical outcome.
Your primary role will be to curate a suite of machine learning tools for the integration and analysis of clinical and multi-omic data from the PanProstate Cancer Group (http://panprostate.org), with the aim to identify and characterise 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 conjunction with our collaborators, we will identify and validate the clinical relevance of these subtypes in terms of both prognosis and treatment options, and develop recommendations for the translation to 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.
You will have a PhD degree or equivalent experience in bioinformatics, computational biology, or a relevant numeric subject, (e.g. computer science, biostatistics), have strong organisational skills and a good track record in publications. You will also have experience in performing machine-learning techniques and experience of managing a project with large amounts of data. Well-developed analytical and practical skills; programming skills; an enthusiasm for working in an interdisciplinary environment and the ability to interact & communicate effectively with scientists from other disciplines including clinicians, scientific computing IT, and biologists is also essential. You should also be able to meet all the essential criteria set out in the Person Specification.
Closing date: 20 January 2020.
Further particulars and an application form can be obtained from: https://myview.uea.ac.uk/webrecruitm...ancyRef=RA1690
Ref: RA1724
£33,797 to £40,322 per annum
The post is offered on a full-time, fixed term basis from 1 March 2020 to 31 August 2023.
We are seeking a highly-motivated senior post-doctoral bioinformatician/data scientist with expertise in machine learning and data integration to take a leading role in an exciting new project "Comprehensive characterisation of prostate cancer subtypes to inform precision medicine” funded by a Prostate Cancer Research Centre grant. This project will expand on previous work where we used our existing machine learning approaches to identify novel prostate cancer subtypes that were informative of clinical outcome.
Your primary role will be to curate a suite of machine learning tools for the integration and analysis of clinical and multi-omic data from the PanProstate Cancer Group (http://panprostate.org), with the aim to identify and characterise 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 conjunction with our collaborators, we will identify and validate the clinical relevance of these subtypes in terms of both prognosis and treatment options, and develop recommendations for the translation to 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.
You will have a PhD degree or equivalent experience in bioinformatics, computational biology, or a relevant numeric subject, (e.g. computer science, biostatistics), have strong organisational skills and a good track record in publications. You will also have experience in performing machine-learning techniques and experience of managing a project with large amounts of data. Well-developed analytical and practical skills; programming skills; an enthusiasm for working in an interdisciplinary environment and the ability to interact & communicate effectively with scientists from other disciplines including clinicians, scientific computing IT, and biologists is also essential. You should also be able to meet all the essential criteria set out in the Person Specification.
Closing date: 20 January 2020.
Further particulars and an application form can be obtained from: https://myview.uea.ac.uk/webrecruitm...ancyRef=RA1690