Machine-learning/AI-based testing and test generation for analog/mixed-
Last modification : Tuesday, November 23, 2021
The PhD research will be carried out under the guidance of Prof. Georges
Gielen (https: // www. esat.kuleuven.be/micas/index.php/georges-gielen), who is
an expert in the design, design automation and testing of analog/mixed-signal
integrated electronic circuits. The work will be performed in the ESAT-MICAS
(Microelectronics and Sensors) research group at the Department of
Electrical Engineering (ESAT) at KU Leuven, Europe's most innovative
university (Reuters, since 2016 till now). ESAT-MICAS is internationally
renowned for its wide range of research, education and valorization activities
in integrated electronics (https: // www. esat.kuleuven.be/micas/). MICAS has
over 80 researchers (postdocs and PhD students) from many different
countries and offers a dynamic, thriving and interdisciplinary environment on
a wide portfolio of research projects.
A PhD position is available within the frame of a VLAIO project of Prof.
Georges Gielen in collaboration with an automotive company. Analog and mixed-
signal electronic circuits are essential in many applications like Internet of
Things, biomedical, automotive, among many others. Especially in safety-
critical applications like automotive, there are extremely tight requirements
on the reliability and robustness of the integrated circuits (ICs): the
circuits may not fail, and any defects introduced during fabrication must be
detected during the testing of the ICs. Since the current techniques used in
industry do not reach the required parts-per-billion (ppb) test escape
levels, novel test techniques must be developed to address this problem.
This job opening covers a PhD research position (4 years) in the frame of
this VLAIO project. The candidate will investigate and explore a novel
techniques to improve the quality and test coverage of test methods for analog
and mixed-signal integrated circuits. Focus will be on investigating and
applying advanced statistical and machine-learning/artificial-intelligence-
based techniques. Also, solutions towards real-time on-chip monitoring and
signal interpretation will be investigated.Second goal is to reduce the time
needed for analog/mixed-signal test program development through novel
techniques for automated test signal generation. The candidate will have to
prototype and validate the methods on actual designs in collaboration with the
Candidates should have a strong expertise in (analog/mixed-signal) IC design
and computer algorithms (in particular methods of optimization, statistics
and/or machine learning/artificial intelligence).
Additional research/development experience in any of the following topics is a
hands-on experience in programming
hands-on experience in design of (analog/mixed-signal) integrated
hands-on experience with methods of optimization and/or machine
Candidates should be motivated, independent, show critical thinking and
scientific curiosity, and should have strong team-player skills.
Required background: Master in Electrical Engineering, Master in Nano
Engineering or Master in Computer Science with proven knowledge of
analog/mixed-signal integrated electronic circuits besides the mastering of
Excellent proficiency in the English language is required, as well as good
communication skills, both oral and written.
The position offers :
A PhD scholarship for 4 years, with a competitive monthly stipend;
An exciting interdisciplinary research environment at KU Leuven, Europe's
most innovative university;
The possibility to participate in international conferences and
The possibility to collaborate with industry.
Interested applicants should submit a motivation letter with a statement why
this project fits with your expertise, a curriculum vitae, the names and
contact information of 2 references.
Please do not postpone submitting your application until the deadline.
Applications are monitored continuously, and it could be that the vacancy
closes before its end date once a candidate has been found.
For more information please contact Prof. dr. ir. Georges Gielen, tel.: +32 16
324076, mail: firstname.lastname@example.org .
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regardless of gender, age, cultural background, nationality or impairments. If
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