Researcher in population and landscape genomics
Position as research fellow available at Department of Biosciences, Section for Genetics and Evolutionary Biology (EVOGENE).
This researcher position will begin as soon as April 2017, but the start date can be flexible. Initial appointment is for two years.
Project description:
The Kauserud´s Lab at the University of Oslo is seeking a motivated Researcher to be part of an ongoing collaborative project investigating the effect of forest fragmentation on the genetic variation of wood-decay fungi throughout Fennoscandia. The research programme FunGen, aims to enhance fundamental knowledge pertaining to the evolutionary processes responsible for generating and maintaining genetic diversity within populations of fungi in order to provide baseline information for improved forest management practices and conservation initiatives. This project is funded by the Research Council of Norway (NFR), under the programme Miljøforsk.
Depending on her/his specific expertise and qualifications, the selected candidate would be responsible for:
- the analysis of a RAD sequencing data set generated from several populations of a wood-decay fungal species. The corresponding genome has been sequenced in collaboration with the Joint Genome Institute. This data set is available and the postdoc/researcher will carry out the bio-informatics & population genomics analyses (Task1).
- both the wetlab and computational analysis of other polypore species sampled on a macro landscape-scale. In this subproject, the postdoc/researcher will work in close collaboration with other partners (NINA, NIBIO and SLU) involved in the landscape analyses (Task 2).
The candidate will also have opportunities for implementing her/his scientific ideas in different subprojects.
Qualifications:
The Faculty of Mathematics and Natural Sciences has a strategic ambition of being a leading research faculty. Candidates for the fellowships will be selected in accordance with this, and expected to be in the upper segment of their class with respect to academic credentials.
The candidate must have obtained by the start date a PhD or other corresponding education equivalent to a Norwegian doctoral degree in ecology, population genetics, evolutionary genomics or bioinformatics.
We seek a highly motivated and skilled person who is able to work independently, to take own initiatives and to have a strong interest in producing high quality research and writing scientific publications. Good writing and communication competencies along with excellent team working traits are highly desirable. The ideal candidate would have experience in preparing libraries for next-gen sequencing (RADseq/GBS), demonstrated bioinformatics skills in 'Big-data' analytical approaches and high expertise in population genetics analyses. The candidate should be familiar with programming languages like Unix and Python/Perl and have advanced statistical skills, preferably in R.
Knowledge of the Norwegian language is not required.
A good command of English is required.
Salary:
Position code 1109, Salary NOK 486 100 – 567 100 per year ( pay grade 57 -65), depending on qualifications and seniority.
The application must include:
- Application letter
- CV (summarizing education, positions, pedagogical experience, administrative experience and other qualifying activity)
- Copies of educational certificates, transcript of records and letters of recommendation
- A complete list of publications and up to 5 academic works that the applicant wishes to be considered by the evaluation committee
- Names and contact details of 2-3 references (name, relation to candidate, e-mail and telephone number)
Please remember that all documents should be in English or a Scandinavian language.
In accordance with the University of Oslo’s equal opportunities policy, we invite applications from all interested individuals regardless of gender or ethnicity.
For more information please click "Further Official Information" below.
This opportunity has expired. It was originally published here:
http://uio.easycruit.com/vacancy/1781463/96323?iso=no