Jobangebot connecticum Job-1764435

DLR-DAAD Doctoral Fellowship Nr. 631: Transfer Learning for Variable Underwater Sensor Setups

Deutsches Zentrum für Luft- und Raumfahrt (DLR)

Jobdatum: 01. Oktober 2024

Einstiegsart: Azubistellen
Einsatzort: Bremerhaven; Bremen
Jobdetails Bewerbungsformular

Info zum Arbeitgeber

Deutsches Zentrum für Luft- und Raumfahrt (DLR)

Wissenschaft & Forschung, Luft- und Raumfahrt, Energie, Verkehr, Sicherheit, Digitalisierung

Firmensprache

Deutsch, Englisch

Gründungsjahr

1907

Mitarbeiter

10.001 - 50.000

Branche

Energie, Forschung

Kontakt

Bei Fragen zu Stellenangeboten aus unserem Jobportal DLR.de/jobs wenden Sie sich bitte an die in den Stellenanzeigen genannten Ansprechpartnerinnen und Ansprechpartner.

Homepage
DLR.de

Karriere-Website
DLR.de/jobs

Doctoral Fellowship
Enter the fascinating world of the German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt; 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!
Our Institute for the Protection of Maritime Infrastructures in Bremerhaven offers a
DLR-DAAD Doctoral Fellowship
Nr. 631: Transfer Learning for Variable Underwater Sensor Setups
What to expect:
The safety and security of critical infrastructures is an essential foundation for the economic prosperity and stability of governments and societies. The Institute for the Protection of Maritime Infrastructures focuses on this challenge and develops new concepts, approaches and technologies that may be used to analyse and enhance the safety and security of maritime infrastructures regarding people, technologies and systems.The Situational Awareness and Cybersecurity Group at the Department of Maritime Security Technologies develops methods for processing and handling of data for novel situational awareness concepts, with a strong focus on machine learning technologies to enable operators to handle large amounts of incoming sensor data.
Join our interdisciplinary research team and develop next-generation security technologies with us! This fellowship focuses on the core question of portability of deep learning algorithms for the processing of underwater sensor data. While deep learning algorithms produce impressive results, they require very large training data sets, which is an issue for fields that cannot easily create vast amounts of data or often alter sensors, such as underwater applications.
In this position, you will
  • focus predominantly on sonar data sets to analyse how various state-of-the-art machine learning and data processing methods behave when the
    training data differs from the test data, e.g. after sensor parameters have been altered or sensors were replaced
  • join our team of scientists in their ongoing task of selecting, analysing and implementing current approaches and methods from the scientific machine
    learning and deep learning communities
  • plan and execute exciting data gathering campaigns in maritime environments
  • compare algorithms concerning the impact of altered input data parameters and publish your research at international conferences and in international journals
The Institute for the Protection of Maritime Infrastructures has committed to principles of open source and open data, allowing results of our research to be
published openly when possible.
What we expect from you:
  • Master’s degree or Diploma in Computer Science, Data Science, Mathematics, Natural Sciences or similar classes excellent knowledge of modern programming paradigms, especially objectoriented and functional languages, such as C++, Python, Java, Scala, Haskell and/or Rust
  • desire to learn new programming skills and techniques
  • experience in the application and implementation of Deep Learning approaches
  • proficiency in the English language both written and spoken
  • analytical and creative thinking for solving complex problems
  • team-minded, communicative and cooperative
  • enjoying interdisciplinary work
  • knowledge of Linux, Windows, Latex, Office
  • version control using git
  • experience in research projects with partners from industry and academia
  • experience in maritime projects and/or with maritime sensors
  • proficiency in the German language both written and spoken
  • experience in managing larger data sets
  • published research papers in topics relevant for this position
  • strong knowledge in algorithms and data structures
  • English competence: See requirements on www.daad.de/dlr
What 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.
Further information:
Starting date: As soon as possible
Type of employment: Full-time
Contact:
Dr.-Ing. Jannis Stoppe
E-Mail: Jannis.Stoppe@dlr.de

Info zum Arbeitgeber

Deutsches Zentrum für Luft- und Raumfahrt (DLR)

Wissenschaft & Forschung, Luft- und Raumfahrt, Energie, Verkehr, Sicherheit, Digitalisierung

Firmensprache

Deutsch, Englisch

Gründungsjahr

1907

Mitarbeiter

10.001 - 50.000

Branche

Energie, Forschung

Kontakt

Bei Fragen zu Stellenangeboten aus unserem Jobportal DLR.de/jobs wenden Sie sich bitte an die in den Stellenanzeigen genannten Ansprechpartnerinnen und Ansprechpartner.

Homepage
DLR.de

Karriere-Website
DLR.de/jobs

Info zur Bewerbung
Jobtitel:

DLR-DAAD Doctoral Fellowship Nr. 631: Transfer Learning for Variable Underwater Sensor Setups

Jobkennzeichen:
connecticum Job-1764435
Bereiche:
Informatik, Mathematik, Naturwissenschaften
Informatik: Informatik
Naturwissenschaften: Mathematik, Naturwissenschaften allg.
Einsatzort: Bremerhaven; Bremen
Jobdetails Bewerbungsformular

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