12/07/2019

Machine-learning-based testing and test generation for analog/mixed-signal ICs


  • ORGANISATION/COMPANY
    KU Leuven
  • RESEARCH FIELD
    Computer scienceModelling tools
    EngineeringElectronic engineering
  • RESEARCHER PROFILE
    First Stage Researcher (R1)
  • APPLICATION DEADLINE
    10/08/2019 23:59 - Europe/Brussels
  • LOCATION
    Belgium › Leuven
  • TYPE OF CONTRACT
    Permanent
  • JOB STATUS
    Full-time
  • HOURS PER WEEK
    38
  • REFERENCE NUMBER
    BAP-2019-484

Many emerging electronic applications, such as the internet of things (IoT) or smart autonomous systems, rely on analog and mixed-signal (AMS) circuits to interface with the physical world (e.g. sensors, radios,etc.). Examples are fields like automotive, biomedical, industry 4.0, etc. Computation in the edge and embedded intelligence are becoming standard practice. In addition, these applications come with extremely demanding reliability and robustness requirements: the circuits may not fail undetectedly. This must be addressed at IC design time (pre-fabrication), at IC test time (post-fabrication) and at run time (during IC usage). Due to their nature and sensitivity, however, the analog parts of AMS systems require significantly more testing effort, compared to their size.

 

This PhD will therefore investigate and explore the emerging capabilities of novel techniques from machine learning and artificial intelligence (AI) towards the efficient testing and test generation for analog integrated circuits. Detecting outlying behavior will be a major focus to maximize test coverage. Also, solutions towards real-time monitoring and signal interpretation in the edge will be investigated.

 

The PhD work will involve the development of novel machine learning/AI techniques and algorithms, and their application to the testing of analog/mixed-signal electronic integrated circuits.

Benefits

The position offers a PhD scholarship for 4 years.

Eligibility criteria

Required background: Master in ElectricalEngineering or Master in Computer Science with proven knowledge of programming/CAD and of analog/mixed-signal integrated circuits.

Selection process

For more information, please contact Prof. dr. ir. Georges Gielen, tel.: +32 16 32 40 76, mail: georges.gielen@kuleuven.be.
You can apply for this job no later than 10/08/2019 via the online application tool

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Work location(s)
1 position(s) available at
Katholieke Universiteit te Leuven
Belgium
Leuven
3000

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EURAXESS offer ID: 426782

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