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Translational Statistician/Data Analyst

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The Institute of Cancer Research

The Institute of Cancer Research, London, is one of the world’s most influential cancer research institutes, with an outstanding record of achievement dating back more than 100 years.

ICR-CTSU is looking for an experienced biostatistician with expertise in correlative science and biomarker research to join the newly-formed Genomic Analysis – Clinical Trial group headed by Dr Cheang, co-inventor of PAM50 classifier for breast cancer intrinsic subtypes, based at the ICR-CTSU in Sutton, Surrey. The post holder will be in a key interface position, supporting initiatives to integrate data analyses of data from next generation sequence (NGS), microarray, digital gene expression profiles, proteomics and immunohistochemical platforms to test important clinical trial correlative biology and preclinical trial development hypotheses.

Our portfolio of national and international trials prioritises activity in three clinical and therapeutic domains:
• Breast cancer systemic therapies and uncommon cancers
• Urological and lung cancer systemic therapies and early phase trials
• Image-guided and local therapies

These priority areas are supported by a cross-cutting biomarker and genomic analysis theme. This theme facilitates interrogation of the wealth of emerging trial data and focuses on the integration and translation of novel diagnostic, prognostic and therapeutic strategies into clinically relevant biomarker driven trial designs. The post holder will focus on the design and analysis of biomarker directed randomised clinical trials and translational research studies associated with the ICR-CTSU’s trials portfolio. The post holder will also have opportunity working as part of a multidisciplinary team on the statistical development, oversight and analysis of a number of multi-centre phase II/III and biomarker-directed cancer clinical trials within ICR-CTSU’s portfolio, and associated issues of design (e.g. multi-stage, adaptive designs; use of Bayesian methodology) and analysis of translational research projects.

The importance of translational research in clinical trials is now widely recognised and many of the ICR-CTSU trials have linked sample collections on which associated biomarker translational research is based. Increasingly, as we pursue a personalised medicine approach to cancer treatment, biomarkers are being used to select potential trial participants and monitor their progress.Applying and developing appropriate statistical methodologies to facilitate novel trial designs and robust analysis of data arising from tissue sample collections associated with large scale clinical trials is a key challenge.

The successful applicant will join a team of statisticians and will work with ICR-CTSU staff and expert colleagues to develop a research program in the statistical aspects of translational/biomarker oncology. Candidates for this post should have be an applied translational statistician with experience in the analysis of biomarker or genetic/genomic data and associated clinical data and excellent communication and organisational skills. You should hold a post-graduate degree.

The position will be offered initially on a fixed-term contract of three years, with the potential for renewal thereafter.
Closing Date 16/11/2018
Contract 3 years, fixed-term, full time - 35 hours per week
Salary Range £35,109 - £42,634

Further information may be obtained by emailing ICR-CTSU at the following address: - ctsu@icr.ac.uk. This email address is for information only.

To apply please follow the link, complete the application form and upload your CV and a supporting statement outlining why you would be suitable for this position including how you meet the person specification
https://icr.tal.net/vx/appcentre-ext/brand-0/candidate/so/pm/1/pl/1/opp/523-Translational-Statistician-Data-Analyst/en-GB


Status: Researcher
Location: London, UNITED KINGDOM
Remuneration: 35109 - 42634 UK Pounds/year
Advert Published: 17 Oct 2018
Expiry date: 16 Nov 2018
The Institute of Cancer Research Ref. No.:
523
Academic Jobs EU Ref. No.:
Please quote this number if applying for this job offline.
J20695
 

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