Minimize Student Internship in Big Data technologies for Remote Sensing Data exploitation

Date added: 24 July 2017

Organisation: Luxembourg Institute of Science and Technology (LIST)

Location: Belvaux, Luxembourg

There are more and more sensors that collect data about our environment. Remotely sensed imagery is one of the most promising, very fast growing sources of such data. The Copernicus Sentinels e.g. will soon produce 10TB of open data per day, such as SAR (Synthetic Aperture Radar) and Optical images of high quality.

This data can be combined with "in-situ" data from airborn devices, and other sources. The exploitation of this data is a huge challenge. The sheer volume is one of the biggest. Furthermore, a lot of "algorithmic intelligence" is necessary to benefit from the new quality of the raw material that comes more frequently, with higher resolution and from more sources.

ERIN is working on many aspects of the necessary innovation in this fast growing domain. From optimized and new algorithms for image processing up to infrastructure and general data analytical platforms for remote sensing and related data. The necessary "Big Data" software infrastructure is investigated, designed and put in place by ERIN's E-Science unit.

The student will contribute to this ongoing effort by examining the state-of-the-art "Big-Data" technologies (based on Hadoop, Apache Spark, In-Memory computing, etc.) in the specific field of the analysis of remote sensing data.


  • The candidate should be preparing or having a master's degree in computer science or related fields (environmental sciences, geo-computing, etc.) with a strong focus on computer science.


  • Good programming skills are expected, knowledge of languages such as R and Python and other "Big-Data" related technologies are considered an asset.

Learn more about the role and how to apply.

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