We are looking for
Plant breeding has progressed enormously over the last decades, but the development of new varieties is very time consuming as it depends on meiotic recombination to generate crossovers and thus genetic variation. In the EU Horizon 2020 INNOVATIVE TRAINING NETWORKS (ITN) programme, the Meiotic Control of Recombination in Crops (MEICOM) project will build on earlier research, in (among others) Arabidopsis and tomato, to study crossover formation in crops and to devise ways of influencing the frequency and location of crossovers. Within this project, you will study meiotic recombination crossover profiles using genome bioinformatics and machine learning methods. Your task will be to analyse crossover formation in crop genomes using novel combinations of high-throughput sequencing (Illumina, PacBio, Oxford Nanopore, 10X Genomics) and optical mapping (BioNano Genomics) data, to learn about crossover frequency in haplotypes, genome structure and structural variation in parental lines and offspring of crops such as tomato, potato, melon, and lettuce. Sequence and genome structural data will be mined using machine learning techniques to find features influencing recombination. With project partners, you will then study the link between structural diversity, genetic diversity and cross over frequency with variation for particular agronomic important traits.
As an ITN researcher, you will be offered a number of secondments to partners (University of Amsterdam; University of Birmingham; SESVanDerHave, Belgium) and enjoy regular ITN meetings. Furthermore, you’ll have the opportunity to actively communicate and promote your research via international meetings and, if applicable, at private parties such as breeding companies.
We are looking for an ambitious, enthusiastic team player and result-driven scientist with:
- an excellent academic record (MSc) in bioinformatics, computer science or a related area;
- demonstrable skills in mathematics, statistics and programming;
- proven proficiency in algorithm development, preferably related to machine learning;
- affinity with genomics and next-generation sequencing data analysis;
- excellent oral and written communication skills in English.
EU ITNs are meant to train young researchers and increase their mobility. Therefore, candidates should have obtained their MSc degree no longer than four years before the starting date (i.e. after March 1, 2014), cannot yet hold a PhD or equivalent degree. Moreover, candidates may not have resided or carried out their main activity (work, studies, etc.) in The Netherlands for more than 12 months in the 3 years immediately prior to the starting date (short stays not taken into account).