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Working Student (f/m/x) - Orbit Classification and Signal Processing
Job Description
Req ID:  1680
Place of work:  Trauen
Starting date:  01.07.2025
Career level:  Student employment
Type of employment:  Part time, Full-time
Duration of contract:  4 - 6 months

Remuneration: Remuneration is in accordance with the Collective Agreement for the Public Sector - Federal Government (TVöD-Bund)

Enter the fascinating world of the German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt e. V.; DLR) and help shape the future through research and innovation! We offer an exciting and inspiring working environment driven by the expertise and curiosity of our 11,000 employees from 100 nations and our unique infrastructure. Together, we develop sustainable technologies and thus contribute to finding solutions to global challenges. Would you like to join us in addressing this major future challenge? Then this is your place!

The German Aerospace Center (DLR) has established a national Responsive Space Cluster Competence Center (RSC³) with the support of the German Federal Ministry of Defense (BMVg). The RSC³ implements the Responsive Space Capabilities research program both inside and outside DLR by exploiting the synergies between civil and defense technology research and building a national network of research, academia, industry and users. 

 

What to expect

In the ground segment department at the Responsive Space Cluster Competence Centre (RSC3) in Trauen we deal with the observation of the space environment. One research topic involves the precise orbit prediction with various machine learning algorithms. The algorithm uses past orbital information and an approximator to compare real data to its approximated counterpart. The student's task is to familiarize himself/herself with the machine learning technique used and implement a signal processing method, that classifies the Satellite in Orbit in either "no maneuvers"; "standard AOCS procedures"; "orbital changes"

 

Your tasks

  • familiarize with existing software
  • understand machine learning techniques and Perturbation Model used
  • implement Orbit Classification using past TLE Date
  • documentation of results
  • option to convert findings into a Master's Thesis

 

Your profile

  • background in natural sciences/mechanical engineering or similar
  • basic programming skills (preferably in Python)
  • basic Knowledge in Orbital Mechanics
  • fluent in German and / or English
  • experience with astronomy/telescopes
  • advanced knowledge in Orbital Mechanics

We offer

DLR stands for diversity, appreciation and equality for all people. We promote independent work and the individual development of our employees both personally and professionally. To this end, we offer numerous training and development opportunities. Equal opportunities are of particular importance to us, which is why we want to increase the proportion of women in science and management in particular. Applicants with severe disabilities will be given preference if they are qualified.

We look forward to getting to know you!

 

If you have any questions about this position (Vacancy-ID 1680) please contact:

 

Marcus Thomas Knopp 
Tel.: +49 8153 28 3720 
Apply now