BOL

van Noort Group is looking for PhD fellows

We currently access an unprecedented knowledge on the basic components making up living systems. An ever growing number of new technologies are being developed with the capacity to systematically measure the behaviour of multiple cellular components, such as biochemical activities, biophysical properties, subcellular localization and interaction. These technologies produce large amounts of raw data that can be transformed into information by software and tools developed both in academia and industry. However, this biological information does not equal biological knowledge. As biology becomes large-scale, new methods have to be developed to integrate, visualize and query the large amounts of information available. This is usually beyond the expertise of experimental labs. The goal of this young computational systems biology group is to generate biological sense from the growing amount of biological data becoming available and turn biological information into biological knowledge. http://www.biw.kuleuven.be/m2s/cmpg/research/CSB

We seek a PhD student who will work as a computational biologist in the interdisciplinary project NATAR. Understanding the relationship between an organism’s genotype and phenotype remains one of biology’s fundamental challenges. In the project two model organisms, budding yeast and E. coli, will be exploited to better understand two complex genetic traits: ethanol and high temperature tolerance. For both organisms both natural variation and the outcomes of experimental evolution will be correlated with phenotypes. The first challenge in the project will be to identify which of the many variants in these genomes have functional effects. Then we will try to facilitate unravelling complex interactions between alleles, for example through functional gene networks that are based on a combination of published data. An important part of the generated data that underlies this project consists of high-throughput sequencing of DNA and mRNA of populations and isolates. For answering specific questions data integration with other data sources will be needed as well as the application of specific machine learning techniques. Basic molecular biology knowledge and basic programming skills are a prerequisite for this position. Experience with high throughput sequencing analysis methods, machine learning, protein interaction databases, perl/python scripting or BioconductoR are preferred. For more information contact prof. Rob Jelier (r.jelier@gmail.com) or prof. Vera van Noort (vera.vannoort@gmail.com). In your application please include a CV describing coursework, grades and previous research experience as well as a minimum of two letters of recommendation.

Starting date: from 1st of October 2013