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Verhulst

6 days ago

Doctoral Fellow in Personalized Audio Signal Processing and Auditory Neuroscience – Department of Information Technology Ghent University in Belgium

Degree Level

PhD

Field of study

Computer Science

Funding

Full funding available

Deadline

December 31, 2026
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Country

Belgium

University

Ghent University

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Keywords

Computer Science
Biomedical Engineering
Signal Processing
Electrical Engineering
Information Technology
Deep Learning
Python Programming
Neuropsychology
Auditory Neuroscience
Hearing Loss
Machine learning

About this position

The Department of Information Technology at Ghent University is offering a fully funded doctoral fellowship in the Hearing Technology Lab, focusing on personalized audio signal processing and auditory neuroscience. This position is part of the European Research Council-funded InSilicoEars project, which aims to develop next-generation, bio-inspired audio technologies by integrating biophysical auditory models with state-of-the-art machine learning approaches. The research will leverage deep neural networks and auditory neuroscience data to create robust, personalized audio solutions for complex, noisy environments.

As a doctoral fellow, you will work within the Hearing Technology Lab, led by Professor Verhulst, collaborating with a multidisciplinary team of biomedical engineers and audiologists. Your responsibilities include developing novel machine-learning methods for personalized and augmented hearing, refining these approaches using neuroscience data, and conducting rigorous technical evaluations and benchmarking. You will optimize computational performance for real-time audio processing and develop hardware demonstrators. Additionally, you will design and conduct sound perception and listening experiments with human participants, and support clinical studies to assess the effectiveness of the developed technologies.

The lab is equipped with advanced computational resources, including local GPUs, CPU servers, and access to high-performance computing clusters. The SOUNDlab core facility provides soundproof booths and integrated EEG and auditory perception setups. The team has a strong track record in research valorization, translating scientific findings into clinical and market applications, with support from the university’s technology transfer office.

Applicants must hold a master’s degree in engineering sciences or informatics (biomedical engineering, computer science, information technology, electrical engineering, acoustics). Required skills include expertise in digital signal processing (audio, biomedical), experience with machine-learning techniques for time-series and frequency-domain processing, and strong programming abilities in Python and MATLAB. Familiarity with machine learning frameworks (Keras, PyTorch), firmware programming languages (C/HDL), and personalized audio signal processing is advantageous. Candidates should be able to work independently, communicate research results effectively, and demonstrate proficiency in English.

The position offers full funding for up to 48 months, with an initial 12-month contract extended upon positive evaluation. The fellowship amount is 100% of the net salary of an AAP member, determined by family status and seniority, and is free of personal income tax. Ghent University provides additional staff benefits, including training opportunities, 36 days of holiday leave, bicycle allowance, and eco vouchers.

To apply, submit your CV, diploma copy, MSc thesis, and motivation letter (including contact information for two referees) to [email protected] before the deadline of June 1, 2026. For further information, contact Dr. Lien Tack at [email protected]. More details about the project and lab can be found at the provided links.

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

More information can be found here

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