Postdoc - Airborne eDNA and Hair Lichens

Postdoc - Airborne eDNA and Hair Lichens

SLU - Swedish University of Agricultural Sciences

Uppsala, Sweden

About the position

We are looking for a postdoctoral researcher for a project studying the effects of climate change on epiphytic hair lichens using airborne eDNA samples. Hair lichens, i.e. lichens of the genera Alectoria, Bryoria, and Usnea are an important part of boreal forest ecosystems, and highly sensitive to drivers of global change. They have been widely regarded as indicators of ecosystem health, and their decline in abundance has been correlated with air pollution and forestry. Climate change poses a new threat to hair lichens, but its effects are so far poorly understood.

This project uses a long time series (ca. 50 years) of eDNA samples collected in the northernmost region of Sweden. With these data, we aim to understand how climate change and other global change drivers influence different species of hair lichens. The postdoc will participate in dataset assembly, field work (hair lichen surveys), data analysis, and writing of the resulting scientific manuscripts. The specific tasks will be adjusted to the skills of the candidate and the overall fit within the research group. The postdoc will be based at the Department of Ecology in Uppsala (Sweden), and the project includes collaborators at other universities, such as Umeå University (Sweden).

Your profile

We are looking for a highly motivated applicant with experience in working with DNA sequence data. Applicants should hold a PhD in biology, ecology, bioinformatics, biotechnology, or other relevant, closely related field. As postdoctoral appointments are career-developing positions for junior researchers, we are primarily looking for candidates with a doctoral degree that is three years old at most.

The applicants are required to have:

• Experience of DNA sequencing data analysis;
• Experience of scripting in e.g. R or Bash;
• Basic bioinformatics skills;
• Good statistical knowledge;
• Good English skills, both spoken and written.

In addition, knowledge or experience of the following are regarded as strongly meriting:

• Lichen or cryptogam ecology, functional traits or ecophysiology;
• Programming in e.g. Python;
• Analysis of very large datasets;
• Genome assemblies;
• Working on computer clusters;
• Time series analysis;
• Mathematical modelling.