In daily life, fingerprints act as the identifier of individuals. Similarly, electronic devices in various application areas (communications, biomedicine, ….) can be categorized according to their fingerprint. The goal is to extract a robust fingerprint from the response of stimulating the electronic device with a well-designed signal. In this project, we focus on high-frequency (microwave/mmwave) excitations that not only cause an electrical response but also trigger underlying multiphysics behavior, in particular due to self-heating. The latter is enriching the RF fingerprint leading to efficient and robust categorization. This hypothesis will be researched by well-optimized experiments and be assessed on RF devices, aqueous liquids, and even plants.

The candidate:

• should have a MSc degree in Electrical Engineering or equivalent;
• should be ranked within the top 10% of their class in MSc and BSc, and have exceptional grades;
• should have a background in microwave engineering and machine learning;
• should have strong communication skills and be fluent in English;
• should have strong interpersonal skills and the ability to work in an international team;
• should be interested in both experimental and theoretical work;
• being a first author or co-author in internationally peer-reviewed publications is a plus.

We offer a PhD scholarship up to four years (subject to positive intermediate evaluations);

You will be working in a multi-disciplinary and strongly international research environment.

For more information, please contact Prof. dr. ir. Dominique Schreurs: dominique.schreurs@kuleuven.be.