postdoctoral scientist
University of Bristol, Bristol
postdoctoral scientist
£43482-£50253
University of Bristol, Bristol
- Full time
- Temporary
- Onsite working
Posted 3 weeks ago, 16 May | Get your application in now before you miss out!
Closing date: Closing date not specified
Job ref: 248d3139aa69492c8727067fb46784f1
Location ref: Bristol
Full Job Description
We are seeking a talented and enthusiastic postdoctoral scientist with experience and a track record in molecular epidemiology. The successful applicant will join our world-leading and highly collaborative multi-disciplinary team of cancer population research scientists at the University of Bristol, based within our Cancer Research UK-funded Obesity-related Cancer Epidemiology Programme (OCEP). Hybrid working is available: an expectation to be on campus for in person meetings as required.What will you be doing? This role will be based within Work package 1: 'Biological Mechanisms' and will investigate key mechanisms linking body-fat distribution to cancer and examine the impact of adiposity across population subgroups (e.g. diverse ethnicities) and cancer subtypes, applying causal inference methods within large-scale population studies. The postholder will be encouraged to develop their own research ideas within the programme; given the opportunity to contribute to teaching and postgraduate training; and will be supported in their career progression. A range of training courses are available, and we actively encourage continuing professional development within the post. Please see this link for further information on some of the courses available: Short courses | Bristol Medical School | University of Bristol.
- Understanding of molecular epidemiological concepts and population health science.
- Detailed knowledge of population-based statistical methods to analyse large, multidimensional datasets.
- Experience of collaborating and corresponding with multiple studies.
- Experience of working on large-scale epidemiological and bioinformatic analysis, including genetic, 'omic and causal inference methods.
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