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Quandela's Quantum Information team seeks a scientist with a strong theoretical background in quantum computing to evaluate near‑ and mid‑term architectures, bridging theory, computation, and hardware constraints. You will develop models and numerical tools, explore architecture‑performance trade‑offs, and collaborate with Architecture, FTQC, and Algorithms teams to shape future roadmaps.
Must have a PhD; proficiency in Python; experience with noise modelling and quantum algorithms; fluent
Quandela is a global leader in quantum computing, designing, building, and delivering cutting‑edge quantum solutions for research and industry. Its offerings include the most energy‑efficient quantum computers for data centers, full‑stack quantum computing solutions accessible via the cloud, and algorithm access services for academic and industrial customers. Following a pragmatic, step‑by‑step roadmap, Quandela has been deploying industrial‑grade systems since 2023 while developing future generations of fault‑tolerant quantum computers capable of scaling through the integration of thousands of photonic components. Quandela is committed to making quantum computing accessible to all in order to address the most complex industrial and societal challenges. Learn more at: Quandela | Leading Photonic Quantum Computing Solutions Our ambition is to build large‑scale fault‑tolerant quantum computers capable of solving problems beyond the reach of classical computation. Getting there will require several generations of intermediate architectures. Choosing the right ones means understanding what can be built, what these systems can compute and how efficiently they can do so.
You will join Quandela's Quantum Information team within Architecture , working on the evaluation and design of our near‑and mid‑term quantum architectures. Your role will sit between quantum theory, computational capability and real hardware constraints. You will develop methods to evaluate architecture concepts, understand their performance and limitations, and help guide future architecture choices. Depending on your background, you may draw on complexity theory, quantum learning theory, quantum‑system characterisation, benchmarking or related areas. You will work closely with our Device Physics, FTQC and Q.Algorithms Team.
As a Quantum Information Scientist working on Architecture & Performance, you will:
We are looking for a scientist with a strong theoretical background in quantum computing, scientific autonomy and an interest in connecting different layers of the quantum‑computing stack.