Home PhD PhD Position in Probabilistic Machine Learning for Audio, KU Leuven, Belgium

PhD Position in Probabilistic Machine Learning for Audio, KU Leuven, Belgium

Postdoctoral Fellow in Belgium

Summary

The PSI division at KU Leuven is offering a fully funded PhD position focusing on probabilistic machine learning for audio applications. This project aims to develop effective audio representations that generalize across cultures and styles. Ideal candidates will merge theoretical advances with real-world applications.

PhD Position in Probabilistic Machine Learning for Audio, Arenberg Campus, KU Leuven, Heverlee, Belgium

Designation

PhD Candidate in Probabilistic Machine Learning for Audio

Table

DetailInformation
Research AreaProbabilistic Machine Learning for Audio
LocationArenberg Campus, KU Leuven, Heverlee, Belgium
Eligibility/QualificationMaster’s degree in Electrical Engineering, Computer Science, or AI; strong foundation in probability theory and machine learning; programming skills; English proficiency required.
Job DescriptionConduct research on audio representations, sequence modeling, and uncertainty quantification; engage in collaborative projects with researchers.
How to ApplySubmit CV, transcripts, contact details for 2-3 referees, and a 1-page motivation letter outlining interest and prior experience to KU Leuven’s online application tool.
Last Date for ApplyApril 30, 2026, 23:59 CET

Research Area

This PhD project will explore advanced techniques in probabilistic machine learning to facilitate audio analysis tasks, focusing on areas such as sequence modeling and information retrieval.

Location

The research will be conducted at the Department of Electrical Engineering on the Arenberg Campus in Heverlee, close to Leuven.

Eligibility/Qualification

  • Educational Background: Master’s degree in Electrical Engineering, Computer Science, or Artificial Intelligence.
  • Technical Skills: Strong understanding of probability theory and machine learning, excellent programming skills.
  • Communication: Proficiency in English, with strong oral and written communication capabilities.
  • Experience: Background in speech or audio signal processing is advantageous.

Job Description

The selected candidate will:

  • Engage in research on audio representation and machine learning for audio applications.
  • Collaborate closely with both internal and external researchers.
  • Work on practical and theoretical aspects of the project.

How to Apply

Interested candidates should submit the following documents via the online application tool:

  • CV
  • Academic transcripts
  • Contact information for 2-3 referees
  • A motivation letter (maximum 1 page) specifying interest in probabilistic machine learning and relevant experience.

Last Date to Apply

All applications must be submitted by April 30, 2026, at 23:59 CET.

For more information, please feel free to contact:

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