PhD in Embedded Software for Dynamic Neural Networks

Karlstad University; Leuven; Sur place; EUR 22 000 - 29 000; Plein temps

Avantages offerts par ce poste

PhD scholarship

Competitive salary

Flexible working conditions

Conference opportunities

Résumé du poste

KU Leuven seeks a highly motivated PhD researcher to join the Embedded Systems unit of EAVISE in Leuven, working on dynamic neural networks for embedded AI. The project explores on-device compression and adaptation of neural networks after deployment, aiming at energy-efficient computing and hardware-software co-design.

You will contribute to runtime-reconfigurable kernels, performance models, and memory-aware deployment on RISCV multicore and heterogeneous platforms.

Qualifications

• Candidates hold a master’s degree in electrical or computer engineering (or equivalent).
• Strong programming experience (C/C++) in embedded field and software engineering/compilers is desired.
• Background in computer architectures and embedded platforms (ARM Cortex-M, NPU, FPGA, embedded GPU).
• Experience with deep learning/AI is a plus.
• Excellent English and strong communication skills are required.

Responsabilités

• Engage in hardware-software co-design for embedded AI systems.
• Develop runtime-reconfigurable neural network software kernels.
• Contribute to on-device optimization and energy-efficient computation.

Connaissances

C/C++ programming

Embedded systems

Computer architectures

Deep Learning

English proficiency

Team collaboration

Formation

Master’s degree in electrical or computer engineering (or equivalent)

Outils

ARM Cortex-M

FPGA

Embedded GPU

NPU

Description du poste

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PhD in Embedded Software for Dynamic Neural Networks

KU Leuven is an autonomous university. It was founded in 1425. It was born of and has grown within the Catholic tradition.

The Embedded Systems unit of EAVISE at KU Leuven is looking for a highly motivated PhD researcher to join a novel research initiative investigating how embedded AI systems can dynamically optimize themselves after deployment. EAVISE is a multidisciplinary research group developing state-of-the-art AI, embedded computing, computer vision, and edge intelligence solutions for real-world applications. The Embedded Systems unit focuses on hardware-software co-design, AI deployment tools, and energy-efficient computing for future intelligent devices.

Project

Modern embedded AI systems rely on Deep Neural Networks (DNNs) running on resource-constrained devices such as wearables, smart sensors, hearables, and IoT nodes. While current deployment methodologies can optimize models before deployment, the resulting software remains static throughout the lifetime of the device. Consequently, energy consumption, memory usage, and computational requirements remain fixed, even when the application or environmental conditions evolve over time.

This project investigates a radically new paradigm for Embedded AI: enabling devices to dynamically compress and adapt neural networks directly on-device after deployment. Inspired by how humans continuously optimize their physical efficiency through training, this project aims to develop software methods that allow deployed neural networks to progressively reduce their resource footprint while maintaining application performance.

The research focuses include: runtime-reconfigurable neural network software kernels for novel embedded systems architecture, performance models for adaptive AI workloads, on-device search and optimization engines for memory-aware deployment, compiler and runtime systems capable of supporting dynamic neural network topologies, energy-efficient embedded AI frameworks targeting RISC-V multicore and heterogeneous computing platforms.

The project combines fundamental research in embedded software and compiler systems with practical validation on state-of-the-art embedded AI hardware platforms. Successful outcomes could significantly extend battery lifetime and enable a new generation of adaptive and sustainable embedded AI systems

Profile

We are looking for highly motivated PhD researchers with a strong interest in hardware-software design for embedded systems and Embedded AI.

• Candidates must hold a master’s degree in electrical or computer engineering (or equivalent). Master's students who expect to graduate by the end of the year are also encouraged to apply.
• Programming experience (C/C++) within the embedded field and/or software engineering and compilers is highly recommended.
• Strong background in computer architectures and embedded platforms (ARM Cortex-M, NPU, FPGA, embedded GPU), e.g., via academic courses and/or project courses
• Research experience (e.g., through a Master thesis work or research internships) is considered a strong asset.
• Experience with Deep Learning and Artificial Intelligence is considered a plus.
• Excellent proficiency in the English language is required, as well as good communication skills, both oral and written.
• Strong interpersonal skills and the ability to work in an international team.

Offer

• A PhD scholarship for up to 4 years (subject to positive intermediate evaluations).
• An exciting research environment, working on the intersection between theory and implementation in a very multi-disciplinary research environment.
• A thorough scientific education in the frame of a doctoral training program, with the possibility of becoming a world-class researcher.
• A competitive salary or tax-free PhD grant, including the reimbursement of commute costs to the workplace.
• Flexible working conditions, upon agreement with the PhD supervisor
• The possibility to participate in international conferences, workshops, and collaborations with top EU and KU Leuven research teams.

For more information please contact Prof. dr. ir. Manuele Rusci, mail: [emailprotected] .

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.

Job details

Title

PhD in Embedded Software for Dynamic Neural Networks

2026-08-31 23:59 (Europe/Brussels)
2026-08-31 23:59 (CET)

Closing on: 2026-09-05 (Europe/Brussels)

Closing on: 2026-09-01 (Europe/Brussels)

Closing on: 2026-11-03 (Europe/Brussels)

Closing on: 2026-09-16 (Europe/Brussels)

Closing on: 2026-09-16 (Europe/Brussels)

KU Leuven is an autonomous university. It was founded in 1425. It was born of and has grown within the Catholic tradition.