Computer Scientist, Geo-infomatician or Similar

Computer Scientist, Geo-infomatician or Similar

DLR - German Aerospace Center

Oberpfaffenhofen, Germany

Your mission:

The department “EO Data Science” at the Remote Sensing Technology Institute (IMF-DAS), located at the DLR in Oberpfaffenhofen is developing novel signal processing and AI algorithms to improve information retrieval from remote sensing data, in particular those from current and the next generation of Earth observation missions and deliver crucial geo-information to address social grant challenges, such as urbanization and climate change.

The Helmholtz Artificial Intelligence Cooperation Unit (HAICU) platform aims to enhance the research within the Helmholtz Association with applied AI methods. For that each research area of Helmholtz operates one HAICU unit to work on short, medium and long term AI projects.

IMF-DAS operates the local HAICU unit “MASTr: HAICU Munich @ Aeronautics, Space and Transport”. It consists of a Young Investigator Group (YIG) in Earth observation and an AI Consulting Team, providing the expertise from Earth Observation, robotics, computer vision and an HPC/HPDA support unit.

The specific research focus of the YIG is “Large-Scale Data Mining in Earth Observation”.

This includes research towards large-scale data indexing and retrieval, especially in peta-scale data archives of former, current, and future EO missions. We expect a strong focus on unsupervised information extraction and anomaly detection.

Based on this concept, the ideal candidate will have a proven track record in fields related to statistic learning, modelling, machine learning and spatio-temporal analysis, interest in geographic observation and an open and collaboration-oriented mindset.

The YIG shall be located at the Remote Sensing Technology Institute (IMF), Oberpfaffenhofen. In addition, the YIG leader will be appointed to the Technical University Munich (TUM) and be granted the attractive status of a “TUM Junior Fellow”, comparable to a junior professor, including the right to be the first supervisor of his/her PhD students (“Promotionsrecht”)

The YIG is set up as a five year tenure track process towards permanent positions starting ideally November 1, 2019 or later.

Applying for this position requires the submission of a scientific research plan of no more than 20 pages covering the following aspects: Presentation of clearly recognizable work packages, important intermediate steps, and milestones with a timetable; Presentation of the planned cooperation and communication structures; Statement on the connection to the Helmholtz program.


  • leadership of the junior research group, including supervision/co-supervision of PhD students;
  • internationally visible novel research;
  • work with large scale EO data;
  • development of algorithms – and possibly a prototype processing system – for spectral-/spatial-/temporal unsupervised learning and anomaly detection;
  • a focus should be on multi-modal (radar, optical) remote sensing time series data;
  • development of preferably generic software solutions;
  • relevant use cases shall be developed, e.g. together with Helmholtz centers of Earth and Environment;
  • a tight co-operation with the co-located AI consultant team is required for mutual benefit;
  • collaboration with the other HAICU units, TUM and other regional, as well as international partners.

Your qualifications:

  • Ph.D. in Natural Sciences, Mathematics or Computer Science with a strong connection to the research topic received in the last two to six years (this period is extended if parental leave was taken after the Ph.D.). Exceptions may be made in special cases;
  • Proven track record of applied AI and ML experience;
  • International research experience. This can be documented by a minimum six-month continuous research stay abroad during the doctoral or postdoctoral studies;
  • Exceptionscan be made for outstanding researchers for whom international mobility may be restricted due to special circumstances (for example because of children);
  • Experience with statistical learning, modelling, spatial and temporal analysis and geographical observations;
  • Extended Knowledge of unsupervised Classification methods of EO data and anomaly and change detection;
  • Experience in scientific project management.

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© EuroJobsites 2019

EuroJobsites is a registered company number: 4694396 VAT number: GB 880 9055 04

Registered address: EuroJobsites Ltd, Unit 8, Kingsmill Business Park, Kingston Upon Thames, London, KT1 3GZ, United Kingdom

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