Working field:
The Remote Sensing Image Analysis (RSiM) Group seeks to hire a Research Associate to conduct research and development in the field of deep learning-based compression of large-scale satellite images. Due to the continuous advances in satellite technology, recent years have witnessed an explosive growth of satellite image archives. To reduce the storage size, satellite images are usually stored in compressed format in the archives. Recently, end-to-end learning-based image compression methods have shown outstanding performance when compared to traditional methods such as JPEG2000. However, most of the existing methods are designed for spatial compression and do not consider the spectral redundancy observed in the satellite images.
The goals of this position are:
1) to develop learning-based 3D compression methods were not only spatial but also spectral redundancies are compressed and
2) to explore satellite image analysis in the 3D compressed domain.
Furthermore, the candidate is expected to publish/present the achieved research results.
The position is open for candidates with a Ph.D. degree but also for candidates with the intention to write a Ph.D. thesis.
This research activity is a part of the ERC-funded project: BigEarth – Accurate and Scalable Processing of Big Data in Earth Observation (http://bigearth.eu/index.html)
Requirements:
- Successfully completed university degree (Master, Diplom, or equivalent) in computer science, engineering, or mathematics.
- Knowledge of methods and theory of machine learning, deep neural networks, and image compression.
- Excellent programming skills (e.g., python) with experience using deep learning libraries
- Excellent English oral and written communication skills; good command of German is required; willingness to extend the German language skills.
How to apply:
Please send your **written*+ application with the reference number and the usual documents to Technische Universität Berlin – Die Präsidentin – Fakultät IV, Institut für Technische Informatik und Mikroelektronik, FG Remote Sensing Image Analysis, Prof. Dr. Begüm Demir, Sekr. EN 5, Einsteinufer 17, 10587 Berlin or by email to [email protected].
Please send copies only. Original documents will not be returned.
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To ensure equal opportunities between women and men, applications by women with the required qualifications are explicitly desired. Qualified individuals with disabilities will be favored. The TU Berlin values the diversity of its members and is committed to the goals of equal opportunities.