2 PhD positions @ BIOBIX

02/06/2020

Position: PhD student @BIOBIX to mine the genome for allele-specific effects

“Big data is the starting point, not the end.” (Pearl Zhu)

The BIOBIX lab of Bioinformatics and Computational Genomics at the Faculty of Bioscience Engineering of Ghent University (Belgium) has a vacancy for a PhD student in bioinformatics/omics data analysis. BIOBIX has major expertise in the advanced analysis of large-scale omics data (hundreds to thousands of samples). We are looking for a highly motivated PhD student to join our forces as soon as possible (September 1st the latest).

Allele-specific expression (ASE) is the generic term for the phenomenon where one of both alleles (in diploid organisms) is expressed to a higher extent than the other one. In health, ASE can be caused by several molecular phenomena, including genomic imprinting and random monoallelic expression. Some loci feature recurrent ASE in disease only, indicating that they are likely to be causally involved, independent of the fact whether the ASE observed is due to copy number variation, allele-specific (epi) mutations, … Despite major relevance in health and disease, common methods to comprehensively study ASE are typically very expensive, prone to artefacts, and blind to the type of ASE.

At the BIOBIX lab, we are currently developing the MAGE suite (Modeller of Allelic Gene Expression) which circumvents these problems by explicit allele-specific statistical modelling of RNA-seq data (or similar) at the population level. The candidate will introduce novel functionality in MAGE and apply this innovative methodological framework to obtain a pan-cancer overview of allele-specific aberrations and their causes. Depending on the applicant’s interests and data availability, other diseases can be studied as well.

As a candidate, you have/are:

  • an MSc degree in Bioinformatics, Bioscience Engineering, Biochemistry and Biotechnology, Statistical Data Analysis, Biomedical Sciences or similar (or will have this degree by September 1st)
  • proficient in scripting (e.g. Python) and biostatistics (R), experience with the statistical analysis of sequencing data and/or machine learning is a plus
  • proficient in English, both written and oral
  • acquainted with molecular biology
  • a drive to answer biological questions by mining huge omics data sets
  • an analytical, critical and independent attitude

We provide an open and stimulating working environment at a top 100 ranking university, in which teamwork, initiative, a critical mindset and originality are highly appreciated. We offer a position for 1 year, which will normally be extended to 4 years.

How to apply?
Candidates should send their CV, a motivation letter (approx. 1 page) and the email addresses of two potential referees to prof. Tim De Meyer (tim.demeyer@ugent.be), by April 1st 2020 the latest. Applicants not meeting the criteria outlined higher will not be considered.

To learn more on our methodological approach (in the context of imprinting), see e.g. Goovaerts et al., Nature Communications 2018 (https://www.nature.com/articles/s41467-018-06566-7).

Position: PhD student at Ghent University, Faculty of Bioscience Engineering

At the Faculty of Bioscience Engineering, Ghent University (Belgium), the BIOBIX lab of Bioinformatics and Computational Genomics (Prof. Tim De Meyer, promoter) and the Thomas Van Leeuwen research group (Dr. Wannes Dermauw, copromoter) have joined forces to develop a novel methodology to identify heritable variation in gene expression (expression quantitative trait loci; eQTLs), using herbivore adaptation as highly relevant case study. We are therefore looking for a highly motivated PhD student, starting as soon as possible.

Background

The identification of heritable variation in gene expression, linked to a phenotype of interest (e.g. crop yield, resistance …) is of major importance in the field of applied biological research. However, the identification of such loci, i.e. eQTLs, currently requires laborious breeding schemes and/or the combination of transcriptomics and DNA genotyping data, leading to a very high cost for comprehensive analyses. As a solution, the group of Prof. De Meyer is currently developing a far cheaper and more robust eQTL scanning methodology through statistical modelling of (solely) RNA-seq data. The applicant will further develop and apply this methodology to identify eQTLs in the spider mite T. urticae genome. T. urticae is a world champion in feeding on different plant species (over 1,100 different hosts) and pesticide resistance. As its small genome has been sequenced, it provides the ideal model organism to study rapid genetic adaptation, the field of expertise of Dr. Dermauw and Prof. Van Leeuwen. By bringing the expertise of both research groups together, the applicant will validate the novel eQTL scanning methodology by showing that it is able to identify eQTLs explaining fast spider mite adaptation. Relevance will be further demonstrated by linking obtained results with already available spider mite omics datasets at the copromoter’s lab through bioinformatics analysis.

As a candidate, you have/are:

  • well acquainted with molecular biology, biostatistics and scripting
  • a drive to answer biological questions by analyzing omics data sets
  • an analytical, critical and independent attitude
  • an MSc degree in Bioinformatics, Bioscience Engineering, Biochemistry and Biotechnology or equivalent (or will have this degree at the beginning of the project); related degrees may be considered but only when sufficient background in molecular biology, biostatistics ánd scripting can be clearly demonstrated
  • proficient in English, both written and oral

Ideally, you are acquainted with the statistical analysis of next generation sequencing or other biological big data. However, note that we focus on answering biological questions and that the ambition to learn and apply expert statistical methods is sufficient to apply.

We provide an open and stimulating working environment in a top 100 ranking university, in which teamwork, initiative, a critical mindset and originality are highly appreciated. We offer a position for 1 year, which will normally be extended to 4 years in case of a positive evaluation. Note that the latter may require application for a FWO/BOF doctoral fellowship.

How to apply?

Candidates should send their CV, a motivation letter (approx. 1 page) and the email addresses of two potential referees to prof. Tim De Meyer (tim.demeyer@ugent.be), by April 1st 2020 the latest.

Relevant publications of the promoters:

Goovaerts et al. A comprehensive overview of genomic imprinting in breast and its deregulation in cancer. Nature Communications 2018. (Introduces methodologically relevant concepts).

Wybauw et al. Long-term population studies uncover the genome structure and genetic basis of xenobiotic and host plant adaptation in the herbivore Tetranychus urticae. Genetics 2019.

Dermauw et al. A link between host plant adaptation and pesticide resistance in the polyphagous spider mite Tetranychus urticae. PNAS 2013. (Plant adaptation and pesticide resistance are intertwined)

Grbic et al. The genome of Tetranychus urticae reveals herbivorous pest adaptations. Nature 2011. (Genome paper spider mite)