This PhD position at KU Leuven, within the EAVISE research group, focuses on developing domain-aware audio representations for low-resource settings. EAVISE is a multidisciplinary group operating at the intersection of artificial intelligence, embedded systems, computer vision, and sound processing, and is part of the Electrical Engineering Department (ESAT) and Computer Science Department at KU Leuven. The project aims to advance audio representation learning by designing model structures and learning objectives that explicitly incorporate domain knowledge, particularly for scenarios where training data is limited and compact models are necessary. Application areas include predictive maintenance, process monitoring, environmental monitoring, and safety-critical event detection. The research will address challenges in data efficiency, computational efficiency, and domain generalization by disentangling sound representations based on signal characteristics. The successful candidate will join an international research environment with access to state-of-the-art infrastructure and benefit from close mentorship, participation in courses, workshops, and conferences, and opportunities for collaboration with academic and industrial partners. The position offers a competitive salary or tax-free PhD grant, with an initial one-year appointment and potential extension up to four years. Candidates are expected to conduct research, contribute to project planning, disseminate findings, assist in supervising Master’s students, and participate in limited teaching activities. Applicants must have a Master’s degree in electrical or computer engineering (or a related field), strong mathematical background, coursework in signal and sound processing, proficiency in Python, and excellent English communication skills. Research experience in sound processing and additional programming skills are advantageous. KU Leuven is committed to diversity and inclusion, providing a supportive and respectful environment for all researchers. The application deadline is December 3, 2025, and applications must be submitted via the online tool.

This PhD position at KU Leuven focuses on domain-aware audio representation learning for low-resource settings, embedded within the multidisciplinary EAVISE research group. EAVISE operates at the intersection of artificial intelligence, embedded systems, computer vision, and sound processing, and is part of the Department of Electrical Engineering (ESAT) and the Department of Computer Science. The group offers a stimulating international research environment, access to state-of-the-art infrastructure, and strong industry and academic connections. The project aims to advance audio representation learning by designing model structures and learning objectives that explicitly incorporate domain knowledge, particularly for scenarios where training data is limited and model compactness is essential. Application areas include predictive maintenance, process monitoring, environmental monitoring, and safety-critical event detection. The research will focus on disentangling sound representations based on signal characteristics, improving data and computational efficiency, and enhancing domain generalization. The successful candidate will conduct research on audio representation learning, participate in project planning and meetings, collaborate with academic and industrial partners, disseminate findings through publications and conferences, and contribute to follow-up research proposals. Additional responsibilities include assisting with Master’s thesis supervision, performing limited teaching activities, and enrolling in the Arenberg Doctoral School’s doctoral training program. Applicants should hold a Master’s degree in electrical or computer engineering (or a closely related field), with strong mathematical skills and coursework in digital signal processing, sound processing, and machine learning. Research experience in sound processing is highly valued, and candidates with above-average grades, awards, or publications are encouraged to apply. Proficiency in Python is required, with MATLAB or C/C++ experience considered a plus. Excellent English proficiency and strong communication skills are mandatory. The position offers a competitive salary or tax-free PhD grant, an initial one-year appointment renewable up to four years, flexible working hours, and opportunities for remote work. The application deadline is December 3, 2025. Applications must be submitted via the KU Leuven online application tool and should include a cover letter, CV, transcripts, and a link to the master’s thesis if available. For further information, contact Prof. dr. Thomas Dietzen at [email protected]. KU Leuven is committed to diversity, inclusion, and equal opportunity, fostering a respectful and socially safe environment for all researchers.