Biostatistician/Statistical Scientist in Oncology, Dept. of Oncology, University of Oxford, UK

Dept. of Oncology, University of Oxford, UK
Job Location
Department of Oncology
Old Road Campus Research Building, Roosevelt Drive
United Kingdom
Grade 7: £30,434 - £37,394 p.a.
Job Description

Applications are invited for a Biostatistician post to join a rapidly developing Bioinformatics Research Core Group, based at the Department of Oncology, University of Oxford.

The purpose of the role is:

  • to contribute to and help lead on the analysis of large-scale data sets in molecular oncology,
  • to provide Biostatistical expertise to the Department and the Core,
  • to contribute to the design of studies, the analysis of data and the development of new analytical methods.

The person appointed will be interacting directly with researchers to help identify project funding opportunities, to maintain the scientific quality and integrity of projects and ensure their timely completion. You will focus on statistical analyses of cancer data sets assessing clinical/phenotypic data, genomics and other *omics biomarkers for association with the risk of disease and its progression.

The successful applicant will have a PhD in Statistics or related discipline or equivalent.  Strong quantitative skills, including experience in analyzing large-scale and high dimensional data (e.g. genomics, epigenomics, metabolomics, array-based technologies) using relevant software (e.g. R) are essential. You should also possess the ability to organize and prioritize your own work, as well as have excellent communication skills, both written and oral. The post will involve interactions with collaborators from such diverse fields as Statistics, Computer Science and Medicine.

See also:

For informal enquiries, contact Dr. Anastasia Samsonova ([email protected]). Please quote reference 118951 on all correspondence.

This is a full time post and is fixed-term until 31 March 2017.

The closing date for applications is 12 noon on 16 July 2015.

A research duo finds that science and technology graduate students who turn away from academic careers do so because of changes in their own interests.

Students whose classmates are interested in science are more likely to think about a career in science, technology, engineering, and mathematics, a new study says.

CNBC reports that the genetic counseling field is expected to grow as personalized medicine becomes more common.

Gladys Kong writes at Fortune that her STEM background has helped her as a CEO.