项目介绍

2026年4月11日

The e-Media Research Lab is a research section of Dynamical Systems, Signal Processing, and Data Analytics (STADIUS) in the Department of Electrical Engineering (ESAT) at KU Leuven. The e-Media Lab’s research includes topics related to signal processing, data analysis, machine learning, and Human-Computer Interaction (HCI). e-Media made significant contributions to critical applications in the domains of Industry 5.0, bio-medical sensing, healthcare, and education. In particular, e-Media is exploring novel tinyML technologies to enhance the intelligence and energy efficiency of resource-constrained devices.

Project

We are seeking an enthusiastic PhD researcher to advance hardware-aware Neural Architecture Search (NAS) that can automatically design efficient deep learning models optimized for specific embedded hardware platforms. These models will be deployed in resource-constrained, standalone devices—such as wearable sensors, assistive robotics, or implantable systems—where real-time performance, energy efficiency, and reliability are critical.
Unlike traditional NAS approaches that are hardware-agnostic, the research will explore how hardware characteristics can be integrated directly into the model design process, enabling neural networks that are both accurate and intrinsically aligned with the capabilities of diverse embedded platforms. This includes studying fine grained hardware behavior, developing efficient mechanisms to evaluate candidate architectures, and designing search processes that adapt as more is learned about the underlying hardware. The resulting framework will support on device intelligence without cloud connectivity, ensuring privacy, robustness, and predictable performance in sensitive healthcare settings.
While next-generation healthcare is the primary focus, the framework will be designed to be modular and adaptable, making it broadly applicable to other real-time embedded AI domains (e.g., automotive, human-computer interaction), where efficient on-device processing is essential. 

Profile

We are looking for a highly motivated PhD researcher with an interest in hardware-aware embedded AI-based algorithms. The applicant should:

• have a Master’s degree in Electrical Engineering,
• be ranked within the top 10% of their class in MSc and BSc, and have exceptional grades,
• have a strong background in AI-enabled signal processing and machine learning algorithms,
• have experience with embedded platforms (e.g., NPU, FPGA, ARM Cortex-M),
• be proficient in programming languages like C, C++ and Python for code development and ML model training and inference,
• demonstrate excellent communication skills and be fluent in English,
• show strong interpersonal skills and the ability to work in an international team.

Offer

We offer:

• A PhD scholarship for up to 4 years (subject to positive intermediate evaluations). If the applicant is non-EER, up to 1 year of pre-doc will also be supported.
• An exciting research environment, working on the intersection between theory and implementation in a very multi-disciplinary research environment.
• A PhD title from a highly ranked university (#1 in Europe in terms of scientific innovation) after approximately 4 years of successful research.
• A thorough scientific education, the possibility of becoming a world-class researcher.
• A KU Leuven affiliation, one of the largest research universities in Europe.
• Working on a state-of-the-art topic with state-of-the-art laboratories.
• The possibility to participate in international conferences, workshops and collaborations with top EU research teams.

Interested?

To apply, please submit the following in the online portal:- A CV mentioning BSc and MSc average grades.- A motivation letter (1 page maximum)- Complete transcripts of Bachelor and Master Degrees (if the MSc degree is not finished yet, please send the most recent transcript).- (if available) IELTS, TOEFL or similar test proving your proficiency in English.For more information please contact Prof. dr. ir. Jona Beysens, mail: jona.beysens@kuleuven.be.You can apply for this job no later than May 21, 2026 via the online application tool

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.

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