Research Fellow (Computer Science/Computer Engineering/Physics/Electronics Engineering)
Core
Develop AI-driven systems for quantum error correction, including LLM-based agents for code discovery and neural decoders for fault-tolerant quantum computing.
Role type
Senior IC research fellow (quantum machine learning)
Builds
AI agents, neural decoders, and simulation pipelines for quantum error correction
Domain
Quantum computing and artificial intelligence
Deliverable
production ML models
Required skills
quantum error correction, fault-tolerant quantum computing, decoding algorithms, deep learning, large language models, circuit-level QEC simulation, HPC/GPU cluster management, research leadership
Preferred skills
FPGA deployment, model compression, open-source software development
Technologies
PyTorch, Transformer-based models, FPGA, HPC, GPU clusters
Responsibilities
Develop LLM-driven agentic systems for quantum error-correcting code optimization; Design scalable neural decoders and benchmark them; Investigate AI-assisted synthesis of fault-tolerant circuits; Develop low-latency decoding methods; Build and maintain open-source software and simulation pipelines; Publish research in leading venues; Lead and mentor a team of PhD, Master's, and undergraduate researchers; Collaborate with academic, industry, and hardware partners.
Seniority
Senior, hands-on IC with mentorship
