TGAC Fellowship Programme in Computational Biology

ORIGINAL: TGAC

The Genome Analysis Centre (TGAC) is pleased to announce the launch of a new, five-year, fellowship programme in Computational Biology. The programme is aimed at outstanding early-career computational biologists and bioinformaticians who wish to establish themselves as scientific leaders within a dynamic research environment. The fellowships will be awarded with a competitive salary and a significant research support grant.

We are seeking candidates with an excellent track record whose interests cover areas of strategic and scientific interest to TGAC, our partners on the Norwich Research Park (NRP) and the BBSRC (please refer to www.bbsrc.ac.uk/strategy).

The Norwich Research Park is a research campus partnership comprised of  

• TGAC, 
• the John Innes Centre, 
• the Institute of Food Research, 
• The Sainsbury Laboratory, 
• the University of East Anglia and 
• Norfolk and Norwich University Hospital. 

The NRP aims to deliver solutions to the global challenges of healthy ageing, food and energy security, sustainability and environmental change. It is an international centre of excellence in life and environmental sciences research with world-class expertise in the research and development pipeline from genomics and data analytics, global geochemical cycles and crop biology, through to food, health and human nutrition. This provides an excellent environment for the development of synergistic research. The successful candidates will be required to develop a research project in collaboration with other researchers within the park. In particular, we encourage proposals that address biological challenges relevant to the NRP that may necessitate:

• New approaches to the analysis and interpretation of research data at scale such as: data visualisation, digital simulations, data integration and the handling of complex datasets arising from high throughput technologies.
• Methods and strategies to address challenges arising in applying next generation sequencing to genomics, transcriptomics, metagenomics and epigenomics.
• Development of novel algorithms for the fast analysis of streaming data, in particular in the context of applications to rapid diagnostics and surveillance.