In this PhD project you will develop personalized audio processing algorithms that run on portable devices. We take inspiration from how the brain works. This research project requires a multidisciplinary approach, based on probabilistic (Bayesian) machine learning, computational neuroscience and software development. Please see this youtube presentation on Natural Artificial Intelligence for more information about our research.
This PhD project is funded by the ROBUST program that aims to develop trustworthy AI tools for today's big societal challenges. One of these challenges concerns improving the participation of hearing-impaired persons in challenging work and social settings. In this PhD project, you will develop Bayesian AI methods that enable hearing-impaired persons to improve (e.g., personalize) their hearing device algorithm through in-situ interactions with an intelligent agent. Your algorithms will be implemented on portable devices and operate under computational and energy-consumption constraints.
An important part of the PhD research will be devoted to contributing to RxInfer (http://rxinfer.ml), which is a toolbox-under-development for automating real-time Bayesian inference. Hence, your work will partly consist of developing and coding fundamental (Bayesian) AI tools, and partly on applying these tools to audio processing applications. Therefore, for a perfect fit with this position, you should have a keen interest and background in quality software development.
You will work in the BIASlab team in the Electrical Engineering department at TU/e. This lab focuses its research activities on transferring a leading physics/neuroscience-based theory about computation in the brain, the Free Energy Principle (FEP), to practical use in engineered devices such as augmented hearing devices. During this project you will closely collaborate with other BIASlab researchers, as well as with project team members at the Human Technology Interaction lab, and with our industrial hearing device partner GN Hearing.
Key areas of interest include Bayesian machine learning, probabilistic graphical models (factor graphs), computational neurosciences, signal processing and software development.
A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:
Eindhoven University of Technology is an internationally top-ranking university in the Netherlands that combines scientific curiosity with a hands-on attitude. Our spirit of collaboration translates into an open culture and a top-five position in collaborating with advanced industries. Fundamental knowledge enables us to design solutions for the highly complex problems of today and tomorrow.
Curious to hear more about what it’s like as a PhD candidate at TU/e? Please view the videos at https://tinyurl.com/2gnqpxbt.
Do you recognize yourself in this profile and would you like to know more?
Please contact the hiring manager prof.dr.ir. Bert de Vries at bert.de.vries[at]tue.nl for more information about the advertised position.
Visit our website for more information about the application process or the conditions of employment. You can also contact HRServices.flux[at]tue.nl.
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We invite you to submit a complete application by using the apply button. The application should include a
Security checks can be part of the selection procedure and admission, both by the university as an employer and by the companies the lab collaborates with.
We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.