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英国伦敦皇后玛丽大学William Harvey 研究所招聘生物统计学博士后

2016年02月24日
来源:知识人整理
摘要:

Postdoctoral BioStatistician

Queen Mary University of London - William Harvey Research Institute

We are seeking to appoint a Post-Doctoral Fellow in Biostatistics to join an integrated, multidisciplinary research team of Scientists and Clinicians, led by Professor Cos Pitzalis, focused on Inflammation and Rheumatology research at the William Harvey Research Institute (WHRI) and partner institutions on our picturesque Charterhouse Square campus. This post is funded by the WHRI Centre for Experimental Medicine & Rheumatology (EMR) http://www.whri.qmul.ac.uk/staff/Pitzalis.html, and appointed candidate in the role of Biostatistician will be aligned closely with the Barts Clinical Trials Unit, Wolfson Institute of Preventive Medicine (http://www.wolfson.qmul.ac.uk/).

Working under the direction of senior medical statisticians (including Professor Peter Sasieni) within the Wolfson Institute of Preventive Medicine, the appointee will serve as a critical conduit between the WHRI and the world renowned biostatistical clinical trial expertise in the Wolfson Institute. The successful candidate will provide leadership on the statistical design and analysis of clinical trials within the EMR, working closely with the WHRI Bioinformatics team to construct a statistical framework for the discovery of biomarkers for patient stratification from diverse genomic and clinical data. The position would particularly suit an ambitious early career researcher with an interest in the application of new biostatistical approaches to genomic medicine in clinical trials (3 years).

Informal enquiries about this posts are welcome and can be made to Prof Peter Sasieni (Biostatistician) (p.sasieni@qmul.ac.uk) or Prof C. Pitzalis (EMR) (c.pitzalis@qmul.ac.uk) or +44 2078828192.

Details about the William Harvey Research Institute, can be found on www.whri.qmul.ac.uk

Further details and an application form can be found at www.jobs.qmul.ac.uk by searching for Job Reference QMUL7736.

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