Hi all, I'm advertising for a 2-year postdoc to work on developing and applying methods for analysis of genome-wide association study data. Applications by 5th October. A summary below, or for more details see this link http://www.au.dk/en/about/vacant-positions/scientific-positions/stillinger/Vacancy/show/1001254/5283/
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Aarhus University is recruiting a 2-year postdoc in statistical genetics based at the Bioinformatics Research Centre (BiRC). The provisional starting date is 1st November 2018.
The postdoc will be jointly supervised by Drs Doug Speed, Manuel Matthiesen and Søren Dinesen Østergaard. There are two broad aims, however the specific projects will be decided according to the interests and experience of the successful applicant.
1 – Application of recently developed methods to genome-wide association study (GWAS) data.
Dr Speed has created the software package LDAK which contains a variety of methods for analysing GWAS data. These include the prediction tool MultiBLUP. A possible project of the postdoc will be applying MultiBLUP to GWAS data for a large number of traits (e.g., from dbGAP, the Wellcome Trust Case Control Consortium or UK Biobank), to compare its performance to that of rival methods such as polygenic risk scores and LDPred, then investigate ways MultiBLUP can be improved.
2 – Development of new methods for analysing GWAS data.
Central to LDAK is a method for estimating the SNP heritability of a trait, the proportion of phenotypic variation explained by all SNPs. To date, SNP heritability has been estimated only for common SNPs (MAF>0.01), but it is currently unknown how best to estimate the contribution of rare SNPs. Therefore, a potential project is investigating how best to estimate the rare SNP heritability of a trait. First the postdoc will test methods using simulated data, then apply the most successful to GWAS data for traits such as schizophrenia, alzheimer's disease and heart failure.
*Requirements*
A PhD degree and strong expertise in statistical genetics is essential. The position will involve analysis of large-scale genetic datasets, so the ideal candidate would be familiar with popular genetic software (e.g, PLINK) and at least one coding languages (e.g. R).
*Supervisors*
Assistant Professor Doug Speed specializes in developing statistical methods for analyzing large scale GWAS data. He has released the software LDAK (www.ldak.org) which contains tools for detecting causal variants, constructing prediction models and better understanding genetic architecture, using both individual-level data and summary statistics. Professor Matthiesen specializes in the analysis of large scale GWAS data and its clinical interpretation. He is a physician by training with a specialization in medical genetics, and has a strong background in genetic epidemiology, biostatistics and molecular genetics.
Professor Søren Dinesen Østergaard is a medical doctor who focuses on psychiatric research. He is particularly interested in translational psychiatry, and the idea that studies should cover the full pathway from discovery in the lab, bench to bedside, bedside to clinical applications, and from clinical applications to healthcare and global health.
*Place of work and associated departments*
The position will be primarily based at the Bioinformatics Research Centre, a department with approximately 50 members focused on the development of statistical models and computational algorithmns to analyse genetic data (www.birc.au.dk ). The position will also be linked to the Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), a consortium in charge of 50,000 cases for autism, ADHD, schizophrenia, bipolar disorder and depression (www.ipsych.au.dk ) and to the Department of Clinical Medicine, Denmark’s largest health science institute (www.clin.au.dk/en ).
The place of work is C.F. Møllers Allé 8, 8000 Aarhus, and the area of employment is Aarhus University with related departments.
If you have any questions about the position or application procedure, please contact This email address is being protected from spambots. You need JavaScript enabled to view it. .
