PhD position on multi-modal sensor fusion for AI-driven rehabilitation and activity assessment

The PhD researcher will be part of the eMedia research lab under the supervision of Prof. Bart Vanrumste. The research group is embedded in the Department of Electrical Engineering (ESAT) of KU Leuven, Europe's most innovative university [Reuters]. Prof. Vanrumste’s research focuses on multimodal sensor integration and machine learning for monitoring of older persons and patients with chronic diseases.
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Project

The research group is presently looking for a motivated PhD candidate to work in the context of an FWO-SBO project “RevalExo” and BOSA project "AidWear" in which the eMedia research lab collaborates with the BruBotics research group from VUB to develop the next generation prosthetics and exoskeletons. These devices have gained significant attention in recent years due to their potential to improve the quality of life for individuals with physical disabilities. Many individuals with disabilities face challenges in regaining motor function and strength. These devices provide a means to address these challenges by offering targeted exercises and therapies that focus on specific muscle groups and movements. In these projects, you will work on the assess functionality of these devices:

• Assess: the device and participant is equipped with sensors which capture relevant physiological, kinematic, kinetic, and context data. These data will be processed with advanced learning/sensor fusion AI-algorithms to provide relevant information about the patient’s physical state and rehabilitation progress.
• The devices will have IOT (Internet of Things) connectivity, enabling remote access to its data and remotely changing the assistance and training settings.

Profile

We are looking for a dynamic and motivated PhD candidate with a strong interest in AI, who is interested in studying how advancements in AI can lead to improved user experience and rehabilitation effectiveness of wearable exoskeletons. The candidate will be responsible for the development of the advanced learning/sensor fusion AI-algorithms and will develop an intuitive dashboard that enables the physical therapists to remotely optimize the assistance and training settings based on the output of the AI-algorithms. The candidate will also contribute to teaching activities related to machine learning or other areas depending on the candidate’s profile. Moreover, the candidate is a team player that enjoys collaborating with people within the research group, the project, and beyond, and has:

• A master's degree in Engineering with a background in mechanical engineering, electrical engineering, computer science, AI, or related field, from a reputable institute, with outstanding study results,
• Programming experience in Python in general, particular experience in common deep learning frameworks (e.g., PyTorch and TensorFlow) would be a benefit,
• The qualities to carry out independent research, demonstrated e.g., by the grades obtained on your MSc thesis,
• An excellent command of the English language, both in spoken and written form,
• Is comfortable assisting in data collection experiments with participants in general but older ones in particular, for which spoken knowledge of Dutch would be a benefit,
• A critical mindset.

Offer

•  A doctoral scholarship of four years and, if successful, a PhD in Engineering Technology,
•  A competitive salary and additional benefits such as health insurance, access to university sports facilities, etc.
•  The opportunity to be active in an exciting and international research environment, engage in research collaborations and participate at international conferences,
•  A full-time employment for four years, with an intermediate evaluation after each year,
•  An excellent doctoral training at the Arenberg Doctoral School in an international environment at a top European university, 
•  A flexible working culture with opportunity of up to 40% remote working.

Interested?

For more information please contact Mr. Benjamin Filtjens, mail: benjamin.filtjens@kuleuven.be or Prof. dr. ir. Bart Vanrumste, mail: bart.vanrumste@kuleuven.be.

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