Researcher in quantitative genetics

A position as a researcher in quantitative genetics of forest trees is available at the Department of Ecology and Genetics, Plant Ecology and Evolution, Uppsala University.

The Department of Ecology and Genetics is an international environment with staff and students from all over the world. Our research spans from evolutionary ecology and genetics to studies of ecosystems. For more information, see

Project description: Our group works on plant population genetics and evolutionary biology with a special emphasis on local adaptation and related questions. We study primarily two groups of plants: the tetraploid weed Capsella bursa-pastoris and its close relatives and forest trees (spruces, birches, larches and poplars). The present position is associated with the EU-funded H2020 B4EST project and more specifically with the development of new breeding strategies and the evaluation of the potential of group selection in forest tree breeding.

Duties: The candidate will be responsible for gathering available data in breeding programs and analyzing them. Population and quantitative genetics data analyses, computer simulations and publishing articles.

Qualifications required: A doctoral degree, or a foreign degree equivalent to a doctoral degree, in within population or quantitative genetics. The applicant is expected to have a solid background in quantitative and population genetics and be familiar with UNIX environments and have experience in standard statistical methods. We attach great importance to personal qualities such as good collaboration skills. Candidates must be able to express themselves very well in spoken as well as written English.

Qualifications desired: Proficiency in relevant programming languages (e.g. bash, Perl, Python, C) will be a strong advantage.

More information and to apply:

Closing date: October, 25 2021

For further information about the position please contact: Professor Martin Lascoux, Martin.Lascoux @ , +46 18 471 64 16.

Image: athree23/Pixabay

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