PhD Fellow in Deep Learning and Satellite Remote Sensing within Maritime Applications

Visual Intelligence at The Department of Physics and Technology, UiT The Arctic University of Norway, Tromsø
Posted: June 25, 2021

The position is a 3-year PhD fellow in the area of innovating maritime surveillance services, and is affiliated with Innovation Area Earth Observation, with close collaboration to the centre partner Kongsberg Satellite Services (KSAT).
The research will be focused, but not limited to, the development of deep learning architectures for object detection in marine environment. Exploring context and dependencies in satellite imagery over a combination of radar and optical satellites is of prime importance, as well as researching new AI solutions to quantify uncertainties in the detections. Advances in utilizing weak and/or noisy labels for learning from limited data will further increase the value of KSAT vast archive of historical data for research.

Requirements Include:

  • Norwegian master degree in physics, mathematics/statistics, computer science, or similar, or a corresponding foreign master degree,
  • Background in signal and image processing,
  • Background in machine learning and automatic data analysis,
  • Experience with remote sensing data analysis (SAR and/or optical),
  • Skills in programming,
  • Fluency in English

Experience with deep learning (through courses, research projects, or similar), including hands-on experience with software tools such as Pytorch and Tensor Flow, will be considered a strength.
Knowledge of pattern recognition and big data processing, plus previous experience in applications related to maritime operations (e.g., ship detection, oil spill), is considered as an asset.

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