PhD - Leuven | Just now
In recent years, the explosive growth of artificial intelligence (AI) has pushed conventional electronic systems to their physical and energy efficiency limits, especially as AI models scale to billions of parameters and demand ever-faster access to vast volumes of data. As AI continues to transform sectors from healthcare and autonomous vehicles to finance and scientific research, the necessity for rapid, efficient, and scalable data movement has become increasingly pronounced. Silicon photonics—a technology that harnesses light to transmit and process information using silicon-based devices—offers a compelling solution to these bottlenecks. By leveraging the inherent advantages of optical communication, such as ultra-high bandwidth, low latency, and minimal energy dissipation, silicon photonics paves the way for next-generation AI hardware architectures capable of sustaining the field’s relentless pace of innovation. The convergence of photonic devices with established CMOS manufacturing processes further enables integration at scale, fostering new opportunities for AI accelerators that are faster, more compact, and energy-efficient than ever before. imec, together with our partners, have achieved wafer-scale fabrication of state-of-the-art optical devices utilizing an in-house 300 mm CMOS pilot line.
This Ph.D. project aims to explore and develop novel integrated III-V microlaser source solutions, aimed at highly efficient and reliable operation at high temperatures, as required for deep integrated with advanced CMOS logic. Various laser cavity and waveguide coupling architectures will be explored including VCSELs and in-plane microlaser designs, aiming at high wall-plug efficiencies and robust operation also in the presence of strong back reflection. Particular attention will be paid to the III-V active layer design, aiming at maximizing high-temperature operation. The most promising designs will be implemented in the imec fab/lab, leveraging emerging wafer-scale GaN and GaAs-based integration technology at imec. Finally, their application in on-chip photonic systems for artificial intelligence and optical interconnects applications will be evaluated.
In this research, the Ph.D. student will:
Required background: Integrated photonics, laser technology, Electronics Engineering or equivalent.
Type of work: 40% modeling/simulation, 40% experimental, 20% literature
Supervisor: Dries Van Thourhout
Co-supervisor: Qingzhong Deng
Daily advisor: Qingzhong Deng
The reference code for this position is 2026-158. Mention this reference code on your application form.