Are you interested in working with methods for tree species classification and prediction of wood assortments? In this position you will be classifying tree species with airborne laser scanning and satellite image data, and predict wood assortments with feedback-loops using imputation of harvester data. Sounds interesting? Come and work with us!
We are now looking for a Postdoc who will work in a collaborative project between the Swedish University of Agricultural Sciences (SLU) and the forest company Stora Enso. The project is part of a larger research cooperation between SLU and Stora Enso (see https://www.slu.se/en/storaenso-collab). You will work with methods for tree species classification using multi-spectral airborne laser scanning and multi-temporal and multi-spectral satellite image data. Wood assortments will be predicted with feedback-loops using imputation of harvester data used as reference data and based on predictions of stem diameter distribution and tree species. The project will be carried out in cooperation with world leading researchers from the Finnish Geospatial Research Institute (FGI).
To be qualified for this position you need a PhD degree of relevance for remote sensing of forests. Knowledge about topics such as numerical programming, signal analysis, and statistics is desirable. In addition, it is an advantage if you have experience in the following areas: spectral remote sensing, processing of laser scanning data, machine learning, and remote sensing applications in Nordic forestry. The applicant is supposed to be able to take own initiatives and work both independently and in a group. The applicant should have good communication skills.
Welcome with your application no later than 2021-02-15.