PhD position Signal Processing for Edge-AI Sensing in Healthy Buildings
PhD position Signal Processing for Edge-AI Sensing in Healthy Buildings
Job description
The European HORIZON-project EdgeAI targets intelligent processing of sensor data at the edge. The 48 partners will develop new electronic components and systems, processing architectures, connectivity, software, algorithms, and middleware through the combination of microelectronics, advanced signal processing and edge computing.
The TU/e research specifically addresses the processing of sensor data in building management. Knowledge on the physical properties of sensors and their imperfections are used to improve performance. Also models for human experience, wellbeing (e.g., the circadian rhythm) and performance (e.g., comfort and effectiveness of lighting) are part of the algorithmic framework. Instead of immediately addressing the issues by generic AI, we plan to explore any prior knowledge in the form of formalized, quantified mathematical models and domain insights. The challenge lies in the combination of statistical signal processing, probability and information theory and Bayesian inference. We plan to extend this to also include the combination of data of many, not always reliable sensors, in configurations that vary over time and between different installations. Sensor configurations and usage patterns widely differ from building to building and even from room to room. Hence, their observations on the underlying processes are also different. Nonetheless, there is a need for reliable deployment in a way that a system already performs well immediately after being switched on for the first time. That is, the algorithms need to be robust to the use of a variety in the use of sensors. Moreover, obtaining feedback from the user makes topics such as semi-supervised online learning, transfer learning and active inference of interest.
The TU/e research specifically addresses the processing of sensor data in building management. Knowledge on the physical properties of sensors and their imperfections are used to improve performance. Also models for human experience, wellbeing (e.g., the circadian rhythm) and performance (e.g., comfort and effectiveness of lighting) are part of the algorithmic framework. Instead of immediately addressing the issues by generic AI, we plan to explore any prior knowledge in the form of formalized, quantified mathematical models and domain insights. The challenge lies in the combination of statistical signal processing, probability and information theory and Bayesian inference. We plan to extend this to also include the combination of data of many, not always reliable sensors, in configurations that vary over time and between different installations. Sensor configurations and usage patterns widely differ from building to building and even from room to room. Hence, their observations on the underlying processes are also different. Nonetheless, there is a need for reliable deployment in a way that a system already performs well immediately after being switched on for the first time. That is, the algorithms need to be robust to the use of a variety in the use of sensors. Moreover, obtaining feedback from the user makes topics such as semi-supervised online learning, transfer learning and active inference of interest.
Specifications
- max. 38 hours per week
- Eindhoven View on Google Maps
:fill(white)/logos/tue-en-wide_acOLN2b.png)
Eindhoven University of Technology (TU/e)
Requirements
The PhD candidate will initially participate in system design of an edge-AI sensing and lighting control system. After an introductory phase the candidate will dive deeper into the fundamental challenges, work with real data but also enhance the theoretical framework of handling data. This requires teamwork with other partners. The candidate is expected to actively contribute to this project as well as to research directions towards scientific breakthroughs in the above challenges. Candidates are expected to hold an MSc degree in electrical engineering, mathematics or physics and to have a solid knowledge of statistical signal processing, probability theory, information theory and artificial intelligence. In your motivation letter, we invite you to specifically address your evidenced interest in combining AI with statistical signal processing or with information theory, and in understanding the underlying physics. The project gives great opportunities for transferring meaningful innovations to industry and for secondments with industrial project partners.
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.
Additional information
About us
Eindhoven University of Technology (TU/e, https://www.tue.nl/en/) is one of Europe's top technological universities, situated at the heart of a most innovative high-tech region. Thanks to a wealth of collaborations with industry and academic institutes, TU/e's research is known for its real-world impact and has worldwide a leading position in effective academic - industrial cooperation. TU/e has around 3,000 employees and 2,300 PhD students (half of which international, representing about 70 nationalities).
The position is in the Signal Processing Group (SPS) at the Department of Electrical Engineering (https://www.tue.nl/en/university/departments/electrical-engineering/). The SPS group has a strong track record not only in signal processing for digital communication, but also for medical applications, automotive and for intelligent IoT systems. The impact of the work of the group is evident from a very close cooperation with industrial partners and from international recognition and awards of the team. In this position, you will work in the team of Prof. Jean-Paul Linnartz, internationally known for work on Security with Noisy Data, personalized Human Centric Lighting to improve circadian rhythms and for wireless communication systems, including LiFi.
Curious to hear more about what it's like as a PhD candidate at TU/e? Please view the video.
Information
For more information about the project and any informal enquiries, please contact Prof. Jean-Paul Linnartz (j.p.linnartz[at]tue.nl)
Visit our website for more information about the application process or the conditions of employment. You can also contact HR Services (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:
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.
Start date: position available now
Eindhoven University of Technology (TU/e, https://www.tue.nl/en/) is one of Europe's top technological universities, situated at the heart of a most innovative high-tech region. Thanks to a wealth of collaborations with industry and academic institutes, TU/e's research is known for its real-world impact and has worldwide a leading position in effective academic - industrial cooperation. TU/e has around 3,000 employees and 2,300 PhD students (half of which international, representing about 70 nationalities).
The position is in the Signal Processing Group (SPS) at the Department of Electrical Engineering (https://www.tue.nl/en/university/departments/electrical-engineering/). The SPS group has a strong track record not only in signal processing for digital communication, but also for medical applications, automotive and for intelligent IoT systems. The impact of the work of the group is evident from a very close cooperation with industrial partners and from international recognition and awards of the team. In this position, you will work in the team of Prof. Jean-Paul Linnartz, internationally known for work on Security with Noisy Data, personalized Human Centric Lighting to improve circadian rhythms and for wireless communication systems, including LiFi.
Curious to hear more about what it's like as a PhD candidate at TU/e? Please view the video.
Information
For more information about the project and any informal enquiries, please contact Prof. Jean-Paul Linnartz (j.p.linnartz[at]tue.nl)
Visit our website for more information about the application process or the conditions of employment. You can also contact HR Services (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 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.
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.
Start date: position available now
Specifications
- PhD
- Engineering
- max. 38 hours per week
- University graduate
- V36.6620
Employer
Location
Interesting for you
Apply for this job
Apply for this job
This application process is managed by the employer (Eindhoven University of Technology (TU/e)). Please contact the employer for questions regarding your application.
Thank you for applying
Please contact the employer for questions regarding your application.
Tip: save this job as favorite in your AcademicTransfer account. This gives you an immediate overview and makes it easy to find the job later on. No account yet? Create it now and take advantage of other useful functionalities too!
Application procedure
Application procedure
Make sure to apply no later than 30 Jun 2023 23:59 (Europe/Amsterdam).