The EAVISE research group at KU Leuven, located on Campus De Nayer Sint-Katelijne-Waver, offers a multidisciplinary environment within the divisions of Processing Speech and Images (PSI) in the Electrical Engineering Department (ESAT) and Declarative Languages and Artificial Intelligence (DTAI) in the Computer Science Department. EAVISE specializes in demand-driven applications of advanced algorithms for artificial intelligence, embedded systems, computer vision, and sound processing, with strong ties to industry and a robust research infrastructure.

This PhD position focuses on modeling and processing audio signals under motion, a challenging area where time-varying delays (known as warping) affect the time axis of audio signals. While stationary audio processing has advanced significantly, motion-induced warping—responsible for effects like the Doppler shift—is rarely explicitly modeled. The project aims to develop novel models and processing approaches for audio signals affected by warping, covering both analysis and synthesis tasks. Methodologies include stochastic signal processing and machine learning, with hybrid physics-guided and data-driven frameworks. Research directions may involve modeling warping interactions with signal transformations, estimating motion parameters from audio, moving-microphone measurements of room acoustics, and efficient synthesis and auralization of dynamic acoustic scenes.

The successful candidate will join the international EAVISE group and benefit from a stimulating research environment, access to state-of-the-art infrastructure, and opportunities for collaboration with academic and industrial partners. The standard PhD duration at KU Leuven is four years, with a starting date as soon as practical, preferably in summer 2026. The position offers a competitive salary or tax-free PhD grant, flexible working hours, and the possibility of remote work. The initial appointment is for one year, with extensions possible up to four years.

Applicants must hold a Master’s degree in electrical or computer engineering (or a closely related field), possess a solid foundation in mathematics, and have coursework in digital signal processing, sound processing, and machine learning. Research experience in sound processing is highly valued, especially for candidates with above-average grades, awards, or scientific publications. Proficiency in Python is required; MATLAB or C/C++ experience is a plus. Excellent English language proficiency and strong communication skills are essential. The candidate will conduct research, participate in meetings, collaborate with partners, disseminate findings, supervise Master’s students, perform limited teaching, and enroll in the Arenberg Doctoral School.

KU Leuven is committed to diversity, inclusion, and equal opportunity. Applications must be submitted online by April 13, 2026. Required documents include a cover letter, CV with GPA and relevant courses, transcripts, and a link to the Master’s thesis if available. For further information, contact Prof. dr. Thomas Dietzen at [email protected].