项目介绍

2026年6月5日

Earth Observation (EO) data presents a unique set of exceptional opportunities and challenges for machine learning research. The vast diversity of ecosystems, large-scale data volumes, continuous coverage across multiple spectral bands, and substantial seasonal and diurnal variations pose significant hurdles. Furthermore, the varying spatial and temporal resolutions create complexities that necessitate innovative solutions. We are seeking a highly motivated postdoctoral researcher for one year to conduct research on foundation models for accommodating Earth Observation.

Potential research topics include, but are not limited to:

• Computationally efficient algorithms for processing large-scale Earth observation data
• Novel self-supervised methods for multi-source, multi-scale Earth observation data, with a focus on the geometry of embedding spaces

The successful candidate will be based at the Department of Geosciences and Natural Resource Management at the University of Copenhagen and will work closely with colleagues at the Department of Computer Science (https://di.ku.dk/english/) as well as the Pioneer Center of AI (https://www.aicentre.dk/).

The postdoc’s duties will include research within machine learning and earth observation as well as teaching. The post may also include performance of other duties.

Further information on the Department is linked at https://ign.ku.dk/english/. Inquiries about the position can be made to Ankit Kariryaa (ankit@ign.ku.dk).

The position is open from 1 August 2026or 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.

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

• 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 21 June 2026, 23:59 CEST