Phd Fellow in Deep Learning and Drone-based Lidar Systems for Assessing Carbon Stocks in Cropland and Forest Areas at the University of Copenhagen

The Department of Geosciences and Natural Resource Management in Faculty of Science at the University of Copenhagen is inviting applications for a PhD position in monitoring the terrestrial carbon storage in natural and conventionally managed ecosystems using the capabilities of Lidar (Light Detection and Ranging) and deep learning technologies.

Despite the strong power of deep learning techniques on extracting patterns from large datasets, and the concurrent realization of the high uncertainty in C stock estimations there is a lack of well-established methods in acquiring and processing Lidar point cloud data of high density with deep learning for accurately monitoring ecosystems’ carbon dynamics. The MapCland project targets exactly this line of research and applies an interdisciplinary approach building upon the combined competences of team partners from the Department of Geosciences and Natural Resource Management (IGN) and the Department of Computer Science (DIKU) at the University of Copenhagen.

Inquiries about the position or formalities regarding the application can be made to Postdoc Katerina Trepekli (atr@ign.ku.dk)
Further details in the attached file.