Postdoc of Deep Learning for Large-Scale GeoScience and sustainability Applications

Climate change, population growth, and environmental degradation as well as management of our agricultural, natural, and urban resources are major challenges influencing the achievement of multiple of the UN’s Sustainable Development Goals. Currently an accelerating amount of geospatial data of immediate relevance are collected by satellites, airplanes, and drones. Such data provides hitherto unseen possibilities for capturing patterns and for generating new understanding of eco- and human systems at the process, regional and global scales. Deep learning methods have been identified as one of the key drivers in this context, and this project is about applying state-of-the-art and developing conceptually new deep learning techniques that are adapted to the specific needs of various challenging learning tasks in the earth and geodata domain.

Taking full advantage of the opportunities derived from these new and overwhelming data sources requires a variety of skills. We are searching for a motivated postdoctoral researcher in machine learning or geosciences, with a dedicated interest in addressing some of these challenges. The position will be opened in the context of a new collaboration between the Department of Computer Science (DIKU) and the Department for Geosciences and Natural Resource Management (IGN) of the University of Copenhagen and will also be connected to the SCIENCE AI Centre. The aim is to initiate new groundbreaking research by applying and extending deep learning methods to extract and to explore relevant information from massive amounts of data.

The successful candidate will have the chance to work on a variety of exciting and challenging tasks within the earth and geodata domain, including:

  • Monitoring changes in climate, land use, and vegetation
  • Detecting faults and fractures in geophysical wavefield data
  • Analysing plant phenotyping and ecosystem structure
  • Detecting of landforms such as beach ridge or coastlines
  • Analysing human movements based on geospatial data

To address these tasks, the candidate will have to deal with very large and very complex data sets including petabytes of satellite or lidar data, which will necessitate the application and extension of complex deep learning models. We seek for an innovative postdoctoral research for a 2 year position, who has obtained a Ph.D. degree from a computer science department (or similar) or a geo-science department with significant experience in machine learning and data analysis of very large data sets. The candidate is expected to contribute to research activities within machine learning for geodata and earth system science as sketched above. The position will be a true collaborative position between the Department for Geosciences and Natural Resource Management or with the Department of Computer Science of the University of Copenhagen, but the exact balance and place of wok will be negotiated with the candidate and depend on the candidates background.

Inquiries about the position can be made to Prof. Claus Beier (, Associate Prof. Thomas Friborg (, or Assistant Professor Fabian Gieseke ( Further information related to the Departments at the Faculty of Science can be found here:

The position is open from 1 October 2019 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. 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.The starting salary is currently up to DKK 430.569 including annual supplement (+ pension up to DKK 73.627). Negotiation for salary supplement is possible.
The application, in English, must be submitted electronically by clicking APPLY NOW below.

Please include:

  • Curriculum vita
  • 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 September , 23:59 GMT+1.

After the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the Interview Committee. You can read about the recruitment process at


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