Postdoctoral position on hearing

Vacancy Reference Number

BAP-2017-67

Closing Date

1 Dec 2017

Salary

Competitive

Address

Leuven, Belgium

Duration

2-3 years fixed term contract

A 2-3 year postdoctoral position is available at ExpORL, Dept. Neurosciences, KU Leuven, Belgium. The goal is to explore the application of deep learning to objective measures of hearing. To fit hearing aids an individual person, we need to measure how well they can hear with and without the device. To make this process automatic, we are exploring the use of EEG-based measures and have achieved some success using linear regression methods. We want to explore the use of deep neural networks for our application, and are looking for a postdoc with experience with deep learning. The ideal starting date is between now and 1 October 2017.

EEG-BASED MEASURES OF HEARING BASED ON DEEP LEARNING

The research group of Experimental Otorhinolaryngology, Dept. Neurosciences is part of the University of Leuven. Leuven is located in the center of Belgium, in the heart of Europe. Our group consists of 3 professors, 5 post-docs and ~30 PhD students.

The main research topics at ExpORL, Dept. Neurosciences are:
* New auditory measurement methods based on auditory brain evoked potentials for improved diagnostics and hearing instruments 
* Speech and music processing for cochlear implants
* Noise reduction for improved speech reception with hearing instruments in adverse and noisy listening environments
* Binaural hearing: signal processing schemes and evaluation procedures for bilateral acoustical and/or electrical hearing instruments
* New electrical stimulation for optimal neural excitation in cochlear implants
* Temporal neural processing in the auditory system

In these studies we focus on the chain of auditory modelling, signal processing, simulation, psychophysical tests, electro-physiological measurements, imaging, lab-implementation, and evaluation with normal hearing subjects and users of hearing aids and cochlear implants. Intensive research has led to fundamental knowledge about hearing with hearing instruments. Based on these studies, new signal processing strategies have been developed that are now used worldwide in the most recent cochlear implant systems and hearing aids. Furthermore, diagnostic and evaluation strategies have been developed that are clinically applied.

Website unit

Responsibilities

• You will conduct your own research project, collaborating with PhD and postdoctoral researchers. The required EEG and behavioural data is readily available for analysis, and new data can be collected if required.
• You are responsible for developing and evaluating deep learning methods to the problem on hand. Particular challenges will be the noisy nature of EEG data and modeling its temporal structure.

Profile

• A PhD on a related topic (machine learning, applied deep learning)
• Preferably at least one publication in an international peer-reviewed journal or high quality conference as the first author
• A strong background in deep learning (and related techniques)
• Some background in (EEG) signal processing
• Willingness to work in an interdisciplinary team
• An interest in auditory perception
• An inquisitive and creative mind, good problem solving skills
• Excellent English proficiency
• Knowledge of auditory neuroscience and psychology of hearing is a benefit

Offer

• Exciting auditory research
• Membership of a world-renowned lab, as part of a motivated interdisciplinary team, with an extensive international network
• Membership of KU Leuven, one of the largest research universities of Europe
• The possibility to take part in international conferences and collaborations
• A competitive salary

Interested?

For more information please contact Prof. dr. Tom Francart, tel.: +32 16 37 98 40, mail: tom.francart@med.kuleuven.be.

You can apply for this job no later than December 01, 2017 via the online application tool

Further Information

http://icts.kuleuven.be/apps/jobsite/vacatures/54068012?lang=en

Contact Details

Prof. dr. Tom Francart, tel.: +32 16 37 98 40, mail: tom.francart@med.kuleuven.be