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Postdoctoral research associate in statistics — university of edinburgh

Edinburgh
The International Society for Bayesian Analysis
Research associate
Posted: 27 July
Offer description

Postdoctoral Research Associate in Statistics — University of Edinburgh

Sep 29, 2017

Applications are invited for a 2-year postdoctoral position based in the School of Mathematics of the University of Edinburgh. The successful candidate will lead the development of statistical tools for early diagnosis of liver cancer using patient serum biomarker data.

They will work closely with Prof Ruth King and Dr Vanda Inacio de Carvalho (School of Mathematics) and Dr Tom Bird (Centre for Inflammation Research). The project will develop individualised threshold models using data from several available studies, providing a unified and robust approach. The successful applicant will also be expected to lead further research grant applications and engage with the School of Mathematics by undertaking relevant teaching and tutoring duties.

Applicants will have completed, or be about to complete, a PhD in Statistics or a related field. The applicant will demonstrate outstanding research potential and excellent programming skills. Desirable knowledge includes (but is not limited to): Bayesian techniques; hidden Markov models; individual longitudinal models; regression techniques and survival analysis. The successful candidate will have excellent interpersonal and communication skills, be highly independent, and committed to research in a fast-moving and competitive field. Experience in teaching and associated activities would be an advantage but is not essential.

All applicants should apply online (http://www.maths.ed.ac.uk/school-of-mathematics/jobs/postdoctoral-research-associate-in-statistics). Only complete applications will be considered. Please upload a CV and a research statement under optional documents and arrange for at least two referees to send letters of recommendation directly to hr@maths.ed.ac.uk by the closing date of 5pm GMT on 31 October 2017.

Salary will be in the range £32,548 – £38,833, depending on experience.

Start date: January 2018.

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