Predicting a phenotype from its genotype: whole genome reverse genetic predictions
Project Understanding the relationship between an organism’s genotype and phenotype is one of biology’s fundamental challenges. In this predominantly computational PhD project, the budding yeast will be used as a model organism to better understand two complex genetic traits: ethanol and high temperature resistance. Based on whole genome sequences, both natural variation and mutations arising in experimental evolution will be correlated with phenotypes. An immediate challenge in the project will be to develop approaches to determine which of the many variants in these genomes are having functional effects. Later, the focus will be on unraveling and predicting epistatic interactions between alleles, for example by working with functional gene networks that are based on a combination of published data. In this project, the student will collaborate with a leading yeast lab, which will generate data by high-throughput sequencing of DNA and mRNA of yeast populations and isolates.
Profile For this position we are looking for an aspiring computational biology scientist, preferably with experience in machine learning, handling large biological datasets and statistical tools such as R. Advanced command of both spoken and written English is mandatory. The applicant should hold a degree that formally qualifies him/her to enter the PhD program of the Leuven Arenberg Doctoral School (http://set.kuleuven.be/phd/).
Offer KU Leuven is a leading research-intensive, internationally oriented university that carries out both fundamental and applied research. It is strongly inter- and multidisciplinary in focus and strives for international excellence. The successful candidate will receive an attractive salary and multiple benefits (including health insurance, access to university infrastructure and sports facilities, etc.). Applicants should submit a letter of motivation, a detailed Curriculum Vitae and two (academic) reference letters, to Rob Jelier (Rob.Jelier@biw.kuleuven.be).