The position is part of the NeuroSensEar cooperation project at the Department of Theoretical Physics 2 at the Ilmenau University of Technology, with extended research stays at the Institute of Communications Engineering at RWTH Aachen University.
NeuroSensEar project (more information):
Over 11% of the EU population is affected by hearing loss, but only 41% use hearing aids due to problems with speech comprehension and device fitting. The aim of the project is to improve acceptance and provision by making hearing aids more powerful and automating their fitting. To this end, neuromorphic approaches and principles of biological information processing are being integrated into the technology, and interactive outputs are being developed for better speech comprehension. This should enable those affected to largely regain their hearing ability. NeuroSensEar is funded by the Carl Zeiss Foundation and brings together TU Ilmenau, the Universities of Jena, Ulm, and Kiel, Fraunhofer IDMT, IMMS, and RWTH Aachen.
Department of Theoretical Physics 2, TU Ilmenau (more information):
We investigate instabilities in lasers caused by optical feedback, injection, or mode coupling, with a focus on charge carrier dynamics in nanostructures. We also investigate how electro-optical systems can be used for hardware-based machine learning. Methods: coupled differential equations, nonlinear dynamics, bifurcation analysis. The focus is on reservoir computing as a hardware-friendly learning method. As part of NeuroSensEar, we are investigating how micro-mechanical resonators with nonlinear dynamics can improve hearing aids as “InSensor reservoir computers.”
Institute for Communications Engineering, RWTH Aachen University (more information):
We analyze audiovisual systems along the entire transmission chain to improve quality and efficiency. We take into account signal quality, perception, user behavior, cognitive performance, Quality of Experience, and resource consumption. Our interdisciplinary research combines engineering, computer science, human-machine interaction, and psychology. We work according to open science principles and cooperate closely with international partners and spin-offs.
Your tasks
Your job tasks includes the following responsibilities:
1. Analysis of existing models of human hearing
2. Comparison of biologically inspired models with machine learning and neuromorphic approaches
3. Integration of these models with methods of signal analysis and evaluation of audio and speech quality as well as speech intelligibility
4. Evaluation of performance in auditory tasks (e.g., localization, object and speaker recognition)
5. Use and extension of existing frameworks such as Auditory Modeling Toolbox, OpenMHA, and TWO!EARS
6. Conducting and analyzing perception tests
7. Development of new modeling approaches to improve prediction accuracy
8. Automated evaluation of sensor systems with regard to perception and signal quality
Your profile
For being part of the selection process is needed:
9. Completed university degree (diploma/master's) and doctorate in audio engineering, electrical engineering, cognitive science, computational neuroscience, acoustics, signal processing, or related disciplines
10. In-depth knowledge in one or more of the following areas: Auditory modeling and psychoacoustics, machine learning and deep learning, neuromorphic systems, signal processing for audio and speech, experimental hearing research, psychoacoustics, perception modeling
11. Very good programming skills (e.g., MATLAB, Python, C++)
12. Very good written and spoken English skills
Following competences are desirable:
13. Experience in conducting, evaluating, and modeling perception tests
14. Independent, structured way of working and ability to work in a team
15. Written and spoken German language skills
Please provide evidence of the qualifications required for the job by certificates and references.
The job is not suitable for part-time employment.
What we offer you:
16. attractive remuneration according to collective agreement (as per TV-L) incl. granting of a special annual payment
17. vacation entitlement of 30 days in the calendar year and additional days off on 24 / 31 December
18. family-friendly, flexible working time model
19. VBL - pension scheme in the public sector
20. wide range of individual training opportunities
21. extensive health and sports programs
22. respectful working environment at a renowned university