What we do
We are passionate about biodiversity and our mission is to contribute to combatting the ongoing biodiversity crisis by providing high-resolution data and computational methods to help us better understand and manage the spatial distribution of biodiversity. Our research is interdisciplinary, including the fields of biology, earth sciences, as well as data science & machine learning.
Biodiversity data
We are developing and applying genetic methods to detect small traces of DNA that organisms leave behind in their habitat (environmental DNA). This provides us with comprehensive biodiversity measures of the species community at a site, which even include the large hidden diversity of species that have not yet been discovered and taxonomically described (the vast majority of species!).
Remote sensing data
In our computational models we apply high-resolution geographic data produced by different remote sensing techniques. Some examples are satellite images or 3D-point clouds from airborne laser-scanning. We use these data to correlate biodiversity measure with the biotic and abiotic environment and to eventually be able to make biodiversity predictions for areas that lack biodiversity data.
Machine Learning
We are actively working on building state-of-the-art machine learning models to learn the complex associations of species with their environment. These models are capable to detect areas that are of high conservation value and can aid in conservation planning and selecting sites for biodiversity offsets. Further, these methods allow us to simulate the biodiversity response to specific management scenarios or other factors such as climate change.
We are hiring!
Currently we are looking for a new postdoc to join our lab.
If you have a background in metabarcoding and/or environmental DNA and are interested in biodiversity research, this position is the one for you! The successful candidate will have the opportunity to further develop their research by collecting and analyzing environmental DNA to measure species richness and other biodiversity metrics at a given site. We are currently working on optimizing existing fieldwork and lab-protocols for this purpose and the advertized position will be partly involved in this effort. The aim is to assess the diversity of multiple organism groups, with a focus on (species-rich) taxonomic groups of fungi and insects. The position includes external bioinformatic support and tutoring and therefore constitutes a great opportunity to further develop your skills in this field. You'll be part of a young and dynamic research group at Uppsala University.
The position is a 2-year contract, funded by the Data-Driven Life Science program (DDLS) with unique training and support opportunities.
Application deadline: March 31st, 2023