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Research Assistant (Geo Data Scientist) (m/f/d) full-time job limited to 31.12.2023 Entgeltgruppe 14 TV-L FU reference code: WiMi_Planet_GeoDataScience

Application deadline: 18.07.2022

The Planetary Sciences and Remote Sensing group at the Institute of Geological Sciences of Freie Universität Berlin is involved in several ESA and NASA space missions to explore the solar system and our neighbouring planets. In the field of terrestrial planets, our group is particularly active with a focus on remote sensing and image processing.
As part of a newly approved externally funded project, we are creating high-resolution large-scale image and terrain model mosaics of the planet Mars, assembled from a large number of individual images from different Mars cameras.


We offer a relaxed working environment and exciting data from Mars!
Webseite: https://www.fu-berlin.de/planets


Job description:
The position is initially limited until 31st of December 2023 (extension might be possible) and is open to scientists from various disciplines (preferably geoinformatics or remote sensing) with a strong computer science background, specifically in computer vision and machine learning with a focus on image processing and pattern recognition.

  • Development of state-of-the-art algorithms from the fields of machine learning/deep learning, statistical modelling and data mining with respect to images and point clouds (e.g., super-resolution, depth-from-single-images).
  • Documentation and publication of the methods in peer-reviewed journals
  • Configuration and testing of the algorithms within an automated pipeline/workflow environment and by means of a batch scheduler on the high-performance compute cluster of the university
  • Application of algorithms from the field of machine learning/statistical modeling for the evaluation of topography and image data.


Requirements:

  • Completed scientific university studies (MA, diploma) as well as doctorate in a geoscientific field or alternatively, in computer science.
  • The requirement of a completed doctorate may be waived if an additional qualification in the field of data science/machine learning with several years of experience can be demonstrated.


(Professional) Experience:

  • At least 1 year experience in data science projects
  • Very good programming skills in Python
  • Experience with methods and application of deep learning and statistical modeling
  • Experience with PyTorch or Tensorflow
  • Confident handling of the command line, Bash and working on Linux servers
  • Experience in handling and processing geospatial data on the command line


Desirable:

  • relevant experience in geo data processing
  • Programming skills also in C++
  • Knowledge of quality requirements for elevation models and high-resolution satellite imagery
  • Experience with data pipeline tools
  • Experience with job schedulers on a high-performance compute cluster
  • Knowledge of creating photogrammetric and photoclinometric elevation models
  • Fluent in English (writing and speaking)
  • Ability to work independently as well as in a team
  • Open-source affinity

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Further Information:

All application quoting the reference code should be addressed as an e-mail to Sebastian Walter: plansec@zedat.fu berlin.de or postal to

Freie Universität Berlin

Fachbereich Geowissenschaften

Institut für Geologische Wissenschaften

FR Planetologie und Fernerkundung

Sebastian Walter

Malteserstr. 74-100

Haus D, 12249 Berlin (Lankwitz)

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