At the M-Group at KU Leuven Bruges Campus, we are driving innovation in interconnected, intelligent mechatronic systems. The research group focusses on making systems reliable by developing new technologies in hardware, software, sensors, mechanical structures, energy systems and artificial intelligence. Modern systems need a holistic view on those 4 components, where we integrate expertise of computer science, electrotechnical engineering and mechanical engineering. M-Group is a multi-departemental research group where computer science, electrical and mechanical engineering expertise is combined. The research group consists of 8 professors and more than 40 researchers (postdocs, phd students or assistants) and is supported by a project coordinator, a research manager and 2 technical staff members. We are based at the KU Leuven Campus of Bruges in the province of West Flanders in Belgium (1 hour train ride from Brussels, 3 hour train ride from Paris). The group has access to state-of-the-art labs with recent machines and robotics and has many collaborations with other labs spread over Belgium.
Website unit
Project
The increasing internal complexity of assistive devices, coupled with the trend toward self-adaptability and the integration of AI and ML, presents significant challenges in ensuring safety throughout the entire lifecycle. This complexity not only extends to the technical aspects but also to the interaction between users and the technology. Traditional hazard-and-risk analysis techniques typically operate under the assumption that random failures of individual components lead to accidents, thereby overlooking these emerging safety challenges. To address this evolving landscape, it becomes imperative to develop novel hazard-and-risk analysis techniques that reframe safety as a control problem, considering both component reliability and the dynamic interplay of human interaction with the system.
In this doctoral position advancing you will develop new techniques to eliminate emerging hazard-and-risk through an analysis that reframes safety as a dynamic control problem, moving away from the traditional component-failure approach. This innovative approach takes into account not only component reliability but also the dynamic interplay between users and the technology, strengthening the safety-assurance case for assistive devices.
Your mission:
- Research and gather field-based use cases for assistive health technology, emphasizing reliable sensors, logic, and communication devices to collect raw data.
- Explore the use of edge computing and distributed machine learning on embedded devices to improve cloud services.
Expected Results:
- Development of guidelines for edge-based algorithms utilizing advanced data processing, including machine learning, to translate data into events and offer actionable insights for symbiotic assistive health technology or technical support teams.
- Design of methodologies and algorithm development to derive relevant information from a network of sensors capturing raw data.
Profile
- We are seeking a highly motivated, enthusiastic, passionate, and communicative researcher who holds a Master of Science degree in electrical engineering, computer science or Mechanical Engineering, with outstanding academic achievements (top 5%).
- You should show a high affinity with embedded systems, sensor networks, Body area networks en signal processing.
- Knowledge of the biomedical application domain is an asset
- You are skilled in development in hardware platforms and embedded software, or are willing to learn
- You have knowledge about current state-of-the-art low power platforms for edge computing (Jetson Nano, STM32, TI MSP430,...)
- You have good communication skills and are able to build a network
- You have a critical mindset and are able to formulate your own research questions
Offer
This position is a Marie Slodowska-Curie scholarship from the European Commission.
We offer:
- A fully funded 3-year PhD scholarship (extendable to 4 years)
- Next to you monthly grant, you have a living allowance to travel abroad and to finanance your secondments. If you have a family, you can obtain a family allowance.
- Specialized doctoral training to boost your expertise.
- Opportunities to collaborate in groundbreaking interdisciplinary research and participate in international conferences.
- Access to state-of-the-art infrastructure and a range of university benefits (health insurance, etc.).
- A dynamic, passionate team of fellow PhD students and test engineers.
Full details can be consulted at https://dn-aerialist.eu/apply-now/
In this topic you will be working together with prof. Georg Rauter of the University of Basel (Switserland) and the company PLUX Biosignals loccated in Lisabon (Portugal).
Link to doctoral position DC5
Link to project website
Interested?
For more information please contact Prof. dr. ir. Hans Hallez, tel.: +32 50 66 48 38, mail: hans.hallez@kuleuven.be or Mr. Dries Vanoost, tel.: +32 50 66 48 88, mail: dries.vanoost@kuleuven.be.
Please apply using the online form at https://dn-aerialist.eu/apply-now/ and put DC5 as your first choice
Don't forget to submit:
- A consice CV
- A motivation letter
- Transcripts of your Bachelor and Master
- at least 2 references which we will contact.
KU Leuven strives for an inclusive, respectful and socially safe environment. We embrace diversity among individuals and groups as an asset. Open dialogue and differences in perspective are essential for an ambitious research and educational environment. In our commitment to equal opportunity, we recognize the consequences of historical inequalities. We do not accept any form of discrimination based on, but not limited to, gender identity and expression, sexual orientation, age, ethnic or national background, skin colour, religious and philosophical diversity, neurodivergence, employment disability, health, or socioeconomic status. For questions about accessibility or support offered, we are happy to assist you at this email address.
