Post Doctoral Researcher in Genetic Dissection of Complex Traits

University of Edinburgh

Deanery of Molecular, Genetic & Population Science

The MRC Human Genetics Unit in the IGMM, University of Edinburgh has a vacancy for a postdoctoral fellow in the field of computational/quantitative genetics and bioinformatics. The post-holder will be supervised by Dr. Albert Tenesa and initially undertake a project collaborative between Dr. Tenesa and Professor Ian Jackson.

The project is using phenotype and genotype data from UK Biobank to understand how genetic variation shapes complex variation in humans, in particular hair colour and associated traits. The successful applicant will have a PhD with relevant experience in quantitative genetics, bioinformatics, statistics, machine learning or related field, be proficient in statistical methodology related to quantitative genetics, bioinformatics and/or functional genomics and be a proficient programmer in appropriate languages.

The successful applicant will work within the quantitative genetics and genomics (QGG) group at the MRC Human Genetics Unit (HGU). The QGG group is based at the MRC-HGU and the Roslin Institute, it is an expanding and young group working on different aspects of quantitative genetics and genomics in human and animal populations. Development of lines of research that could lead to successful applications for independent funding will be supported.

Informal inquires could be addressed Albert Tenesa (Albert.Tenesa@ed.ac.uk) or Ian Jackson (ian.jackson@igmm.ed.ac.uk).

The MRC-HGU has a vibrant research community working on multiple aspects of human genetics. The MRC-HGU offers a high-quality research environment with world-class research facilities. The multi-disciplinary environment at MRC-HGU includes, among others, quantitative geneticists, statistical geneticists, epidemiologists, bioinformaticians, biologists and clinicians working in humans and model organisms.

For more information and to submit an application, please use the ‘apply’ button below.

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