Offer 44 out of 75 from 02/03/23, 17:34


Tech­ni­sche Uni­ver­sität Ber­lin - Faculty IV - Institute of Computer Engineering and Microelectronics / Remote Sensing Image Analysis

Research Assistant - salary grade E13 TV-L Berliner Hochschulen - For qualification

part-time employment may be possible

Working field:

The Remote Sensing Image Analysis group ( in the context of BIFOLD ( conducts basic and applied research in data management and machine learning for Earth observation (EO). Currently, we are seeking to hire a Research Associate in field of the development of image search and retrieval methods and systems for querying large-scale satellite image archives. Developed methods will aim at enabling accurate and scalable image indexing and retrieval by efficiently characterizing the complex spectral and spatial content of satellite images. Teaching tasks are required.


  • Successfully completed university degree (Master, Diplom or equivalent) in computer science, computer engineering or a related field
  • Experience in machine learning, distributed systems and database technologies
  • Solid programming skills
  • Familiar with at least one deep learning framework (tensorflow, caffe, pytorch)
  • Excellent command of English; the ability to teach in both German and English is required

How to apply:

Please send your written application with the reference number and the usual documents (in particular a complete CV and certificates) 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

Please send copies only. Original documents will not be returned.

By submitting your application via email you consent to having your data electronically processed and saved. Please note that we do not provide a guarantee for the protection of your personal data when submitted as unprotected file. Please find our data protection notice acc. DSGVO (General Data Protection Regulation) at the TU staff department homepage: or quick access 214041.

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.