Postdoc in Machine Learning for Large-scale Tree Ecosystem Monitoring Full-time

Postdoctoral Position In Machine Learning For Large-scale Tree Ecosystem Monitoring

The Machine Learning Section at the Department of Computer Science (DIKU) invites applications for a two-year postdoctoral position in Machine Learning for Large-scale Tree Ecosystem Monitoring within TreeSense: Center for Remote Sensing and Deep Learning of Global Tree Resources. The TreeSense center is funded by the Danish National Research Foundation and focuses on the critical role of trees in terrestrial ecosystems, such as climate regulation, biodiversity support, and local livelihoods.

The postdoc's duties will include research within machine learning applied to remote sensing data. The postdoc is expected to work together with researchers at DIKU and IGN, the Department of Geosciences and Natural Resource Management at the University of Copenhagen.

The start date is 1 June 2026.

The postdoc will investigate machine learning (ML) methods for analyzing Earth observation data. This can include the development of novel algorithms and learning paradigms. Initially, there will be an emphasis on studying vertical vegetation structure.

Candidates applying for this position must have a strong background in ML, as for example demonstrated by a PhD in Computer Science in the field of ML, with a drive towards advancing the UN sustainable development goals. They must have demonstrated the ability to tailor modern ML frameworks to solve computer vision and ML tasks. Experience in handling Earth observation data is a must. Knowledge in handling LiDAR data, combining multi-modal data, and working with sparsely labelled data are desirable skills. Familiarity with high performance computing systems is a plus.

Principal supervisor is ELLIS fellow Prof. Christian Igel, igel@di.ku.dk, DIKU. Co-supervisors are Assistant Prof. Ankit Kariryaa, ak@di.ku.dk, and Assistant Prof. Nico Lang, nila@di.ku.dk, from DIKU along with Associate Prof. Martin Brandt, mabr@ign.ku.dk, and Professor, Rasmus Fensholt, rf@ign.ku.dk, from IGN.

The TreeSense project The research center aims to revolutionize global tree monitoring using advanced 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 ground 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 will enable 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 two-year position is open from 1 June 2026 or as soon as possible thereafter.

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.

Salary, pension and other conditions of employment are set in accordance with the Agreement between the Ministry of Taxation and AC (Danish Confederation of Professional Associations) or other relevant organisation. Currently, the monthly salary starts at 39,200 DKK/approx. 5,200 EUR (November 2025 level). Depending on qualifications, a supplement may be negotiated. The employer will pay an additional 18,07 % to your pension fund.

Foreign and Danish applicants may be eligible for tax reductions, if they hold a PhD degree and have not lived in Denmark the last 10 years.

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

Please include

• Curriculum vitae
• Diplomas (Master and PhD degree or equivalent)
• Research plan – description of current and future research plans
• Complete publication list
• Separate reprints of 3 particularly relevant papers

The deadline for applications is 1 March 2026, 23:59 CET