Offene Doktorandenstelle (TVL-E13/100 %) im Rahmen der industriegeförderten Graduiertenschule Intelligente Methoden für Test und Zuverlässigkeit (GS-IMTR) an der Universität StuttgartVollpromotion

  • Deutsch, Englisch

    Arbeitssprache

  • Stuttgart

    Standort

  • 30. Sep. 2027

    Bewerbungsende

  • schnellstmöglich

    Antrittsdatum

Überblick

Anzahl offener Stellen

1

Laufzeit

schnellstmöglich für 3 Jahre

Bewerbungsfrist endet am

30. Sep. 2027

Finanzierung

Ja

Art der Promotion

Vollpromotion

Arbeitssprache
  • Deutsch
  • Englisch
Erforderlicher Abschluss

Master

Studienfelder

Angewandte Informatik, Technische Informatik, Informatik, Theoretische Informatik, Informationstechnik, Elektrotechnik

Beschreibung

Beschreibung

GS-IMTR, which is a joint endeavor between the University of Stuttgart and Advantest, an industry leader in automatic test equipment, focuses on topics such as design for test and diagnosis; post-silicon validation; test generation and optimization; robust device tuning; system-level test; lifetime test and reliability management; and test automation. Further information can be found under https://www.gs-imtr.uni-stuttgart.de/.

 

The position to be filled is located at the Institute of Smart Sensors at the University of Stuttgart (https://www.iis.uni-stuttgart.de/). We are looking for candidates holding a Master’s degree (or equivalent) in electrical engineering, computer science, physics, or related subjects interested in pursuing research as part of GS-IMTR’s project P14: Intelligent Sensing and On-Chip Learning for Silicon Lifecyle.

 

Here, project P14 explores the challenges that silicon lifecycle management introduces into the chip design process and, more importantly, the opportunities that it brings to the area of test. In particular, we will focus on the possibilities associated with digital on-chip sensors combined with edge AI in the tester to collect and process the data very efficiently at run-time. Further, we will also investigate the possibility of on-chip online learning on the collected data. The project also involves the developing of a test program for a state-of-the-art data converter, including the collection and processing of statistically relevant data.

 

The candidates should have a strong background in machine-learning and FPGA programming and be familiar with mixed-signal integrated circuit design.

 

What we offer:

  • The possibility to conduct cutting-edge research as part of GS-IMTR
  • Strong interactions with the company Advantest throughout the project
  • A stimulating research environment with more than 20 Ph.D. students working on a broad range of IC design topics for various applications in smart sensing for biomedical and materials science applications as well as quantum technologies
  • The possibility of obtaining a Ph.D. degree from one of Germany’s leading technical universities
  • Access to all state-of-the-art IC design tools
  • Large experience in IC manufacturing
  • A fully equipped mixed-signal lab for chip characterizations
  • Access to state-of-the-art cleanroom manufacturing technologies via a strong collaboration with IMS CHIPS in Stuttgart
  • Collaborations with leading industrial and academic partners
  • Competitive annual gross salary – depending on experience level – of >45.000€ 

What we expect

  • The ability to work in a team
  • Flexibility and dedication
  • Strong motivation to introduce innovations into a current research topic
  • Experience in machine learning
  • Experience in FPGA programming
  • Experience in analog and mixed-signal integrated circuit design
  • Strong background in microelectronics or a similar field of study
  • Curiosity to expand your knowledge into interesting applications
  • Very good knowledge of the English language 

Erforderliche Dokumente

Erforderliche Dokumente
  • Motivationsschreiben
  • Lebenslauf
  • Zeugnisse, Zertifikate
  • Transkripte
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