The Wellcome Trust Centre for Human Genetics, Roosevelt Drive, Headington, Oxford
Grade 7: £29,541 to £33,230p.a.
Applications are invited for a Postdoctoral Research Scientist in Statistical Cancer Genomics to join a newly established research group headed by Dr Christopher Yau based at the Wellcome Trust Centre for Human Genetics (http://www.well.ox.ac.uk/~cyau/). The research will focus on developing statistical methods for the analysis of whole genome cancer sequencing data including modelling tumour heterogeneity and integrative approaches for combining data from multiple sources.
The position would suit a candidate who is interested in developing a career at the interface of statistics and the biosciences. Ideally, you will have experience of statistical methods development gained through a PhD (or equivalent) in a quantitative subject (e.g. mathematics, statistics, physics, engineering or computer science). Experience of Bayesian statistics or machine learning techniques is highly desirable as is evidence of prior experience of developing bioinformatics software and/or analysing genetic data sets.
You will be able to work as part of a team and independently and deliver results to the required standard and schedule. You should also possess the ability to organise and prioritise your own work with minimal supervision and have excellent communication skills, both written and oral. The post will involve interactions with collaborators from Statistics and in Medicine and the Biological Sciences.
The post is fixed-term for 2 years initially and is available from January 2014 (or as soon as possible thereafter) with the possibility of an extension for a further year. Funding is provided by the Medical Research Council with generous provisions for equipment and travel expenses.
Please quote reference 110102 on all correspondence. You will be required to upload a CV and supporting statement as part of your online application.
Only applications received before 12.00 midday on Monday 2 December 2013 will be considered.
To apply, search for Vacancy ID 110102 at the University of Oxford Jobs website
Grade 7: £29,541 to £33,230p.a.
Applications are invited for a Postdoctoral Research Scientist in Statistical Cancer Genomics to join a newly established research group headed by Dr Christopher Yau based at the Wellcome Trust Centre for Human Genetics (http://www.well.ox.ac.uk/~cyau/). The research will focus on developing statistical methods for the analysis of whole genome cancer sequencing data including modelling tumour heterogeneity and integrative approaches for combining data from multiple sources.
The position would suit a candidate who is interested in developing a career at the interface of statistics and the biosciences. Ideally, you will have experience of statistical methods development gained through a PhD (or equivalent) in a quantitative subject (e.g. mathematics, statistics, physics, engineering or computer science). Experience of Bayesian statistics or machine learning techniques is highly desirable as is evidence of prior experience of developing bioinformatics software and/or analysing genetic data sets.
You will be able to work as part of a team and independently and deliver results to the required standard and schedule. You should also possess the ability to organise and prioritise your own work with minimal supervision and have excellent communication skills, both written and oral. The post will involve interactions with collaborators from Statistics and in Medicine and the Biological Sciences.
The post is fixed-term for 2 years initially and is available from January 2014 (or as soon as possible thereafter) with the possibility of an extension for a further year. Funding is provided by the Medical Research Council with generous provisions for equipment and travel expenses.
Please quote reference 110102 on all correspondence. You will be required to upload a CV and supporting statement as part of your online application.
Only applications received before 12.00 midday on Monday 2 December 2013 will be considered.
To apply, search for Vacancy ID 110102 at the University of Oxford Jobs website