PhD Position in Audio Signal Processing and Machine Learning at KU Leuven University of Leuven in Belgium

The University of Leuven (KU Leuven) is offering a PhD position in Modeling and Processing of Audio Signals Under Motion, based at the De Nayer (Sint-Katelijne-Waver) Campus within the EAVISE research group. This multidisciplinary group is part of the Electrical Engineering Department (ESAT) and collaborates with the Computer Science Department, focusing on state-of-the-art algorithms for artificial intelligence, embedded systems, computer vision, and sound processing.

The research project aims to develop novel models and processing approaches for audio signals affected by motion-induced warping, addressing both audio analysis and synthesis. The work will span stochastic signal processing and machine learning, including hybrid physics-guided and data-driven frameworks. Research directions include modeling the interaction between warping and signal transformations, estimating motion parameters from audio, moving-microphone measurements of room acoustics, and efficient synthesis of dynamic acoustic scenes.

Applicants should have a Master’s degree in electrical or computer engineering (or a closely related field), with a strong foundation in mathematics and coursework in digital signal processing, sound processing, and machine learning. Research experience in sound processing is highly valued, and proficiency in Python is required. Additional experience with MATLAB or C/C++ is a plus. Excellent English language skills and strong communication abilities are essential.

The successful candidate will conduct research, participate in project meetings, collaborate with partners, disseminate findings through publications and conferences, and assist in supervising Master’s students. Enrollment in the Arenberg Doctoral School and completion of its coursework requirements are mandatory. The position offers a competitive salary or tax-free PhD grant, with an initial one-year contract and possible extension up to four years. Benefits include comprehensive scientific education, mentorship, access to research infrastructure, opportunities for courses and conferences, flexible working hours, and possible remote work.

The application deadline is April 13, 2026. Interested candidates should apply via the Science HR portal, following the provided link and instructions. Mention Science HR in your application.