PhD in Active Inference for Manufacturing Processes

Introduction

Are you interested in developing cutting-edge AI that is inspired by how the brain works In this PhD project you will apply active inference a leading neuroscientific theory for how the brain works to continuous model alignment for manufacturing processes.

Job Description

In manufacturing uncertainties may arise from stochastic machine behavior sensory noise changes in environment/context and incomplete information. Real-time adaptation to such disturbances is crucial to the efficiency and effectiveness of the manufacturing process. Active inference is a first-principles theory about how agents act and adapt under uncertainty.

By combining active inference principles with probabilistic graphical modeling event knowledge graphs and physics-informed neural nets you will enable agents to reason under uncertainty test hypothesis and adjust internal models based on observed data. These techniques should provide full decision traceability ensuring explainability and accountability of developed agents for application in complex manufacturing processes.

This PhD project is funded by the Horizon Europe program ( You will work in the BIASlab team () in the Electrical Engineering department at TU/e. This lab focuses its research activities on transferring Active Inference principles to practical use in industrial contexts. Please see this youtube presentation ( for more information about our research. During this project you will closely collaborate with other BIASlab researchers as well as with project team members in the Process Analytics Cluster ( and with our industrial partners.

An important part of the PhD research will be devoted to contributing to RxInfer ( 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 manufacturing applications.

Key areas of interest include Bayesian machine learning probabilistic graphical models (factor graphs) computational neuroscience manufacturing processes and software development.

Job Requirements

• A masters 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: manufacturing (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 addition we offer you:

• Full-time employment for four years with an intermediate assessment after nine months. You will spend a minimum of 10% of your four-year employment on teaching tasks with a maximum of 15% per year of your employment.
• 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 P (min. 3059 - max. 3881).
• 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 childrens day care and sports facilities.
• Unlimited access to the modern oncampus TU/e Student Sports Center at an exceptionally affordable rate.
• 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.

On our website you can discover even more information about our conditions of employment. Build on your career at TU/e!

About us

We are a leading international university where scientific curiosity meets a hands-on mindset. We work in an open and collaborative way with high-tech industries to tackle complex societal challenges. Our responsible and respectful approach ensures impact today and in the future. TU/e is home to over 13000 students and more than 7000 staff forming a diverse and vibrant academic community.

Our university is located in Brainport Eindhoven a worldleading tech region with more than 7000 hightech companies and strong R&D activity. Known for breakthroughs in AI photonics semiconductors and advanced manufacturing Brainport is a place where technology serves people and society. Learn more about the Brainport region here.

The mission of the Department of Electrical Engineering is to acquire share and transfer knowledge and understanding in the whole field of Electrical Engineering through education research and valorization. We work towards a Smart Sustainable Society a Connected World and a healthy humanity (Care & Cure). Activities share an application-oriented character a high degree of complexity and a large synergy between multiple facets of the field.

Research is carried out into the applications of electromagnetic phenomena in all forms of energy conversion telecommunication and electrical signal processing. Existing and new electrical components and systems are analyzed designed and built. The Electrical Engineering department takes its inspiration from contacts with high-tech industry in the direct surrounding region and beyond.

The department is innovative and has international ambitions and partnerships. The result is a challenging and inspiring setting in which socially relevant issues are addressed.

Information

Do you recognize yourself in this profile and would you like to know more Visit our website for more information about the application process. You can also contact dr. Thijs van de Laar at for more information about the advertised position. Please note that you can only apply online (see below) and applications sent by email will not be processed.

Curious to hear more about what its like as a PhD candidate at TU/e Please view the video.

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. Kindly note that we may reach out to references at any stage of the recruitment process. We recommend notifying your references upon submitting your application.
• 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.

Ensure that you submit all the requested application documents. Please note that incomplete applications may not be considered and could be rejected.

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.

Please note

• You can apply online. We will not process applications sent by email and/or post.
• A pre-employment screening (e.g. knowledge security check) can be part of the selection procedure. For more information on the knowledge security check please consult the National Knowledge Security Guidelines.
• Please do not contact us for unsolicited services.