RA position in Computational Biology / Bioinformatics for Systems Biology
University of Sheffield
Chemical and Biological Engineering
Closing Date: 14 July 2011
Chemical and Biological Engineering is a thriving department within the University’s Faculty of Engineering and is experiencing a period of considerable growth in both our research and teaching.
The Chemical Engineering at the Life Science Interface (ChELSI) Institute is located within the Department of Chemical and Biological Engineering. Inhabiting newly extended and refurbished state of the art laboratory and office space, the institute aims to foster interactions between the various traditional fields of Life Sciences and Engineering. The institute possesses a strong record in high-throughput data generation (specifically mass-spectrometry-based, quantitative proteomics), Systems Biology and more recently, Synthetic Biology and provides a multidisciplinary environment for modelling and engineering in the life sciences, including medical applications.
You will contribute the theoretical tools for modelling biological systems and analysing biological data. It is expected that you will have a strong background in mathematical modelling and programming, and will possess a broad range of skills, including, statistical / bayesian modelling, programming, working with heavy datasets, network analyses, numerical methods, biological databases, etc. Applicants should have a PhD in Systems Biology, Bioinformatics, Computational Biology, Computer Science or a related discipline (or have equivalent experience). The work will require a creative, independent mind to tackle problems of:
* Network integration of high-throughput data (transcriptomics, proteomics, metabolomics)
* Statistical modelling of quantitative proteomics dataset(for example, multilevel, bayesian, etc.)
* Strategies for inverse metabolic engineering through quantitative proteomics
* Systems biology modelling
This is a ChELSI-funded position and will run for a fixed term, completing on the 30 June 2012.
More information can be found at http://www.jobs.ac.uk/job/ACU777/research-associate-in-computational-biology-bioinformatics-for-systems-biology/