The Scholarship

The Quantitative Systems Biology group, within the Clinical Sciences Centre of the Medical Research Council and the Faculty of Medicine of Imperial College in London (UK), is seeking postdoctoral candidates with a motivated interest in interdisciplinary research, aimed towards a quantitative understanding of the function of complex biological systems. The successful applicant will investigate the quantitative and systems-level properties of signalling, genetic and transcriptional networks in mouse and human T lymphocytes, carrying out projects that integrate experimental measurements with data analysis and mathematical modelling.

The successful candidate will have recently completed a Ph.D. in a biological discipline with a strong publication record. In addition, a sound knowledge of the standard laboratory techniques of molecular and cell biology is expected, as well as experience with immunoassays, flow cytometry and handing of primary cells. Familiarity with high-throughput methods for the analysis of genomes, transcriptomes or proteomes and a working knowledge of mathematical and computational methods will be advantageous. We are a recently established and expanding research lab seeking enthusiasm, flexibility and willingness to learn across disciplines.

Additional information can be found on our website http://qsb.csc.mrc.ac.uk. Informal enquiries about the research projects are particularly encouraged and should be made to Dr Alberto Polleri, Group Head, at polleri@csc.mrc.ac.uk

This post is a Career Development Fellowship to support post-doctoral scientists in early or changed career training and help establish them as a successful and independent research scientist in their chosen field. It is a 3-year training and development post, which incorporates both scientific and transferable skills training.

Application Deadline : 28 May 2010

Web Link

http://mrcserec01.headoffice.mrc.ac.uk/sap(bD1lbiZjPTQwMCZkPW1pbiZwPTM1ODMx)/bc/bsp/sap/zhrrcf_req_dovr/application.do?rcfContext=MEDRES&PARAM=UkVRX0hST0JKRUNUPTAxTkI1MDI1NjQ4NQ%3d%3d