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Thomas Dietzen

Top university

11 months ago

PhD Position on Domain-Aware Audio Representations for Low-Resource Settings KU Leuven in Belgium

Degree Level

PhD

Field of study

Computer Science

Funding

Available

Deadline

Dec 3, 2026

Country flag

Country

Belgium

University

KU Leuven

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Keywords

Computer Science
Electrical Engineering
Mathematics
Artificial Intelligence
Computer Vision
Audio Processing
Python
Embedded System
Low-resource Setting
Machinelearning
Design Models
Signalprocessing
Digital Signal Processing

About this position

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.

Funding details

Available

What's required

Applicants must hold a Master’s degree in electrical or computer engineering or a closely related field, with a strong foundation in mathematics (e.g., matrix algebra) and coursework in digital signal processing, sound processing, and machine learning. Research experience in sound processing is highly valued. Above-average grades, awards, or scientific publications from thesis work are encouraged. Proficiency in Python is required; experience with MATLAB or C/C++ is a plus. Excellent English language proficiency and strong oral and written communication skills are mandatory.

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Professors

Prof. dr. at KU Leuven

University Name
Country flag

Belgium

Research Interests

Artificial Intelligence

Embedded System

Computer Science

Electrical Engineering

Mathematics