PhD on on Bayesian Generative AI for Audio Processing

Job description

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.

Job Description

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.

Job requirements

• A master’s degree in electrical engineering, physics, computer science or similar (this is mandatory).
• A record that shows specific interest in any or more of the following fields: signal processing, (Bayesian) machine learning, professional software development.
• Good written and spoken command of English (C1 level or better).
• A team player attitude, willingness to work hard and know how to have fun at it.

Conditions of employment

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:

• Full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months. You will spend 10% of your employment on teaching tasks.
• Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale 27 (min. €2,541 max. €3,247).
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
• An excellent technical infrastructure, on-campus children's day care and sports facilities.
• An allowance for commuting, working from home and internet costs.
• A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.

Information and application

About us

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.

Information

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.

Are you inspired and would like to know more about working at TU/e? Please visit our career page.

Application

We invite you to submit a complete application by using the apply button. The application should include a

• Cover letter (max 1 page) in which you describe your motivation and qualifications for the position.
• Curriculum vitae, including a list of your publications and the contact information of three references. Please include a description of your background and interest in high-quality software development.
• If you have written a MSc thesis (or published a scientific paper) in English, please send it along with your application or provide a download link.
• If you have written open-source software code, please provide a download link.

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.