[AUDITORY] PhD position in bio-inspired machine learning for audio @ Ghent University, Belgium

[Sarah Verhulst <000001beeac2dfe6-dmarc-request@xxxxxxxxxxxxxxx>]

Dear List,

I am pleased to announce a fully funded PhD position at Ghent University as part of the ERC project InSilicoEars. Please forward to interested Msc students within your network.

https://www.ugent.be/en/work/scientific/doctoral-fellow-102

With best regards,

Sarah

Last application date

Jun 01, 2026 23:59

Department

TW05 - Department of Information Technology

Degree

Master’s degree in engineering sciences or informatics (biomedical engineering, computer science, information technology, electrical engineering, acoustics)

Occupancy rate

100%

Vacancy type

Research staff

ABOUT GHENT UNIVERSITY

Ghent University is a world of its own. Employing more than 15.000 people, it is actively involved in education and research, management and administration, as well as technical and social service provision on a daily basis. It is one of the largest, most exciting employers in the area and offers great career opportunities. 
With its 11 faculties and more than 85 departments offering state-of-the-art study programmes grounded in research in a wide range of academic fields, Ghent University is a logical choice for its staff and students.

YOUR TASKS

The Hearing Technology Lab of iBME is recruiting a predoctoral researcher in engineering for the European Research Council-funded project InSilicoEars. This project aims to harness the unique properties of human auditory processing to develop a new generation of personalized audio solutions that perform robustly in complex, noisy environments. InSilicoEars integrates state-of-the-art machine learning approaches in audio signal processing, such as dCoNNear, with auditory neuroscience data from both normal and impaired hearing. The goal is to build a comprehensive suite of biophysical auditory system models that will drive the development of next-generation, personalized, and bio-inspired audio technologies. 

Your role is to leverage biophysical auditory models within DNN-based closed-loop systems to develop novel machine-learning approaches for personalized and augmented hearing. You will refine these methods using available neuroscience data and conduct rigorous objective and technical evaluations, including benchmarking against relevant challenges. You will also optimize computational performance to enable real-time processing and develop hardware demonstrators. In addition, you will design and conduct sound perception and listening experiments with human participants to validate the proposed approaches. Supporting clinical studies to assess the effectiveness of these technologies will form an integral part of your responsibilities. Throughout these activities, you will collaborate closely with other members of the InSilicoEars team, including biomedical engineers and audiologists. The ultimate goal of your research is to obtain doctoral degree at the faculty of Engineering and Architecture from Ghent University. 

The Hearing Technology Lab at Ghent University is led by Prof. Verhulst and currently hosts a team of 10 researchers. The lab develops pioneering, multi-method approaches to unravel the mechanisms of hearing loss, build biophysically inspired auditory models, and apply innovative machine learning techniques to advance next-generation audio processing. The lab is equipped with 6–8 local GPUs, multiple CPU servers, and extensive storage capacity, as well as access to UGent’s high-performance computing clusters. Additional support is provided by the SOUNDlab core facility, which offers soundproof booths and integrated EEG and auditory perception setups. The team has a strong track record in research valorization, translating scientific findings toward clinical and market applications, with dedicated support from the university’s technology transfer office. More information about the project, the lab, and recent publications can be found here: 
https://cordis.europa.eu/project/id/101232287
https://www.waves.ugent.be/hearing-technology
https://www.ugent.be/ea/ibme/en/research/hearing-technology
https://scholar.google.com/citations?user=gm5wuzUAAAAJ&hl=nl

WHAT WE ARE LOOKING FOR

• You hold a master’s degree in engineering sciences or informatics (biomedical engineering, computer science, information technology, electrical engineering, acoustics). 
• You are an expert in digital signal processing (audio, biomedical) and have experience with machine-learning techniques for time-series and frequency-domain processing. 
• You have strong programming skills in signal processing (Python, MATLAB) and experience with machine learning (Keras, PyTorch). Knowledge of firmware programming languages (C/HDL) is a plus. 
• Prior experience with personalized audio signal processing is a plus. 
• You can work independently in problem solving, searching for the relevant background literature and in leveraging relevant existing techniques to reach your end goal. 
• You can communicate your research results to different audiences (team members, technical reports, research conferences) and work well in a team. 
• Good written and spoken English skills are required, as demonstrated by previously written technical reports and oral presentations.

WHAT WE CAN OFFER YOU

• We offer a full-time position as a doctoral fellow, consisting of an initial period of 12 months, which - after a positive evaluation, will be extended to a total maximum of 48 months. Funding for the full 48-month period is available through the ERC-InSilicoEars project, provided the positive evaluation at month 12. 
• Your contract will start on September 1st 2026 at the earliest. 
• The fellowship amount is 100% of the net salary of an AAP member in equal family circumstances. The individual fellowship amount is determined by Team Personnel Administration based on family status and seniority. A grant that meets the conditions and criteria of the regulations for doctoral fellowships is considered free of personal income tax. Click here for more information about our salary scales 
• All Ghent University staff members enjoy a number of benefits, such as a wide range of training and education opportunities, 36 days of holiday leave (on an annual basis for a full-time job) supplemented by annual fixed bridge days, bicycle allowance and eco vouchers. Click here for a complete overview of all the staff benefits.

INTERESTED?

Send your cv, copy of your diploma (if already in your possession), a copy of your Msc thesis and a motivation letter including contact information of two referees to wavesadmin@xxxxxxxx. 

We do not accept late applications. 

As Ghent University maintains an equal opportunities and diversity policy, everyone is encouraged to apply for this position.

 
For more information about this vacancy, please contact Lien Tack (Lien.Tack@xxxxxxxx).

Sarah Verhulst

Full Professor

 

Hearing Technology@WAVES

Dept. of Information Technology

Ghent University

 

T +32 9 33 14 844

T +32 9 264 33 21 (secretariaat)

Technology Campus, iGent, Technologiepark 126, 9052 Zwijnaarde (BE)

www.waves.intec.ugent.be/hearing-technology

www.gasp.ugent.be

www.github.com/hearingtechnology

www.earditech.com

@hearingtechlab

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