CENTRALE LYON - Post-doctoral researcher (12 months) Mathematics of energy-efficient AI: diffusion models on emerging hardware
CENTRALE LYON€34.4K/yr
Applying for CENTRALE LYON - PhD Silicon Photonics for Scalable Energy-Efficient AI Hardware Accelerators at CENTRALE LYON? Compare this live job with your resume first.
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Role overview
The rapid expansion of artificial intelligence (AI) applications across cloud and edge environments is driving the need for highly efficient hardware capable of supporting increasingly demanding workloads. Among these, matrix multiplication – particularly General Matrix Multiplication (GEMM) – remains the dominant computational kernel in modern AI models, including deep neural networks and transformer architectures. Conventional electronic accelerators, while highly optimized, face growing challenges related to energy consumption, data movement, and scalability. Silicon photonics has emerged as a promising technology to address these limitations by enabling highbandwidth, low-latency, and potentially energy-efficient computation through optical signal processing. In particular, recent advances in photonic computing leveraging phase-change materials (PCM) offer new opportunities for imple
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What they are looking for
Qualification
This PhD is part of the CAMELIA program (ASIC and Numérique agencies) within the targeted project LEAF, and aims to explore a hybrid photonic–electronic computing paradigm for AI acceleration; A major aspect of the PhD will be the development of system-level evaluation and benchmarking methodologies within a design-technology co-optimization (DTCO/SDTCO) framework; In addition, the PhD will address electronic circuit design challenges associated with photonic accelerators, including interface circuits for control, programming of PCM elements, optical-to-electrical readout, and signal conversion; Environment: The PhD will be carried out at the INL laboratory, within the CAMELIA program, as part of the LEAF project, in collaboration between leading academic and institutional partners in AI hardware and photonics
Department · INL - Institut des Nanotechnologies de Lyon
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