PhD position in machine-learning-based automated synthesis of analog/mixed-signal integrated circuits

Katholieke Universiteit Leuven

Belgium

August 28, 2021

Description

PhD position in machine-learning-based automated synthesis of analog/mixed-

signal integrated circuits

(ref. BAP-2021-619)

Last modification : Wednesday, July 28, 2021

This PhD research will be carried out under the guidance of Prof. Georges Gielen (https: // www. esat.kuleuven.be/micas/index.php/georges-gielen), who was awarded the AnalogCreate ERC Advanced Grant and who is an expert in the design and design automation of analog/mixed-signal integrated electronic circuits. The research will take place in the ESAT-MICAS (Microelectronics and Sensors) research group at KU Leuven, which is internationally renowned for its wide range of research, education and valorization activities in integrated electronics (https: // www. esat.kuleuven.be/micas/).

Website unit

Project

Within the frame of the ERC Advanced Research Grant AnalogCreate (https: // www. kuleuven.be/english/research/EU/p/horizon2020/es/erc/analogcreate), several PhD positions and one postdoc position are available. While analog and RF electronic circuits are essential in many applications like IoT, biomedical, automotive, etc., their design remains time consuming and error prone due to their complexity and lack of automation. The overall goal of the AnalogCreate research program is to drastically increase the productivity, optimality and correctness of designing integrated analog electronic circuits by investigating and applying innovative algorithmic techniques, including AI and machine learning. Emphasis is on the autonomous self-learning of the design constraints and expertise.

This PhD position will investigate and explore novel techniques from machine learning and artificial intelligence (AI) towards the automated synthesis of analog and mixed-signal integrated circuits. Focus is either on circuit sizing and/or on circuit layout. Challenges in the research are in the self-learning and auto-extraction of the design constraints and design expertise needed to obtain trustworthy, high-quality synthesis results.

Profile

Required background:

Master inElectrical Engineering, Master in Nano Engineering or Master in ComputerScience with proven knowledge of analog/mixed-signal integrated electroniccircuits besides the mastering of programming/CAD/AI techniques.

Good mastering of spoken and written English.

Offer

The position offers a PhD scholarship for 4 years.

Interested?

For more information please contact Prof. dr. ir. Georges Gielen, tel.: +32 16 32 40 76, mail: georges.gielen@kuleuven.be.

KU Leuven seeks to foster an environment where all talents can flourish, regardless of gender, age, cultural background, nationality or impairments. If you have any questions relating to accessibility or support, please contact us at diversiteit.HR@kuleuven.be.