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technologies for quantum photonic networks? We are now strengthening our research team on quantum light sources in silicon and are opening three PhD positions within fabrication, characterization, and theory
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in catalysis, Power-to-X, and nuclear energy solutions. We design and develop new functional materials, contribute to advances in geosciences and life sciences, and we develop and exploit quantum
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models that integrate data from quantum simulations and experiments, using techniques such as equivariant graph neural networks with tensor embeddings. We aim to train these methods in a closed-loop
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aspects. The project will also explore efficiency and post-quantum security, aiming to bridge theoretical advances with their relevance to practical applications. You will join the growing cryptography team