PostDoc in Remote Sensing and Deep Learning of woody ecosystem properties Part-time

Postdoc Positions In Remote Sensing And Deep Learning Of Woody Ecosystem Properties

The Department of Geosciences and Natural Resource Management invites applicants for two PostDoc positions in Remote Sensing and Deep Learning of woody ecosystem properties. The PostDocs will be part of Center for Remote Sensing and Deep Learning of Global Tree Resources (TreeSense) funded by the Danish National Research Foundation. TreeSense focuses on the critical role of trees in terrestrial ecosystems, such as climate regulation, biodiversity support, and local livelihoods.

The research center aims to revolutionize global tree monitoring using advanced nano-satellite technology and next-generation deep learning (DL) methods within AI. This approach will enable detailed assessment of global tree dynamics, including key functional and structural properties such as important species, the use of trees, tree horizontal and vertical structure, carbon stocks and carbon sequestration rates.

This research paves the road towards addressing science questions on major unknowns within global change research. Here the center will break new grounds on how global warming and increased climatic extreme events affect tree physiology and growth patterns at species level and we will quantify the extent and dynamics of anthropogenic forest disturbance and degradation.

Ultimately, this research enables us to uncover the potentials for various forest and tree-related production systems and human livelihoods as means of climate mitigation actions while improving our understanding of the importance of woody resources for sustainable food systems.

The role of the PostDocs will be to develop research techniques for improved assessment and monitoring of woody vegetation ecosystem properties at the level of single trees based on relevant remote sensing technology and AI algorithms, with a focus on disturbances and change dynamics of trees outside forests.

Specifically, the first position will be responsible for using newest deep learning techniques to further exploit the use of Landsat data including the panchromatic band, potentially leveraging higher spatial resolution of outputs, to be used for studies of the impact of global environmental change. This includes setting up downloading and processing pipelines, as well as operating high-performance compute (HPC) systems and requires extensive programming skills and proven experience in handling high resolution data at scale.

The second position focuses on the development of new deep learning methods, exploiting multi-modal data, to characterize and quantify global tree properties and traits in regard to physiology, morphology, horizontal and vertical forest structure complexity and forest use. This position requires proven experience in large-scale tree/forest mapping both at the level of individual trees and at patch-level. The position requires extensive programming skills and proven experience in handling large quantities of high resolution data.

Research partners are LSCE in France and CREAF in Spain, as well as several Chinese universities.

Formal requirements

Applicants should hold a PhD degree in Geography, Geoinformatics, Environmental Sciences, or related. We are seeking a highly motivated and ambitious individual with good interpersonal and communication skills. Fluency in spoken and written English is a requirement. As criteria for the assessment, emphasis will also be laid on previous publications, relevant experience in remote sensing and forest monitoring, as well as on programming skills (e.g. r, python). Proven experience with high-resolution imagery and machine/deep learning techniques are expected as well as proven experiences with handling and processing large image datasets.

Work environment

Your work place will be the Department of Geosciences and Natural Resource Management (IGN), which conducts research and education on the past, present and future physical, chemical and biological environments of the Earth and their interactions with societal and human systems to provide graduates and research in support of sustainable future solutions for society. The department has strong experience in interdisciplinary collaboration within and beyond the department.

Further information on the Department is linked at https://www.science.ku.dk/english/about-the-faculty/organisation/. Inquiries about the position can be made to Vivian Kvist Johansen.

The positions are open from May 1st 2026 or as soon as possible thereafter and will be available for 4 years.

The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.

Terms of employment

The position is covered by the Memorandum on Job Structure for Academic Staff.

Terms of appointment and payment accord to the agreement between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State.

Negotiation for salary supplement is possible.

The application, in English, must be submitted electronically by clicking APPLY NOW below

Please include

1. Cover letter
2. Curriculum vitae
3. Research plan – description of current and future research plans
4. Complete publication list
5. Diplomas (Master and PhD degree or equivalent)
6. Separate reprints of 3 particularly relevant papers

The deadline for applications is February 28th 2026, 23:59 GMT +1.

Interviews will be held during week 13, March 2026.