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for scalable qubit architectures. Qualifications · For Theorists: o PhD in quantum information, theoretical physics, computer science, or related fields. o Strong background in quantum algorithms, error
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mathematicians, and domain scientists Develop software that integrates machine learning and numerical techniques targeting heterogeneous architectures (GPUs and accelerators), including DOE leadership-class
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based architecture with 2D-connectivity Migration to industrially fabricated devices Your Profile: Master and PhD in physics or a related field In-depth experience with quantum control experiments
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Send your CV along with a motivation letter to chloe.lehoucq@pasteur.fr with benjamin.devauchelle@pasteur.fr in Cc. The candidate should have a PhD in Neuroscience or Cognitive science and the
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candidate will play a central role in engineering fibrillar composite architectures that mimic PTFE performance while introducing recyclability and regulatory compliance. Your Tasks: Develop and characterize
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requirements should be implemented; design and propose architecture and operations concepts and propose recommendations on the most promising technologies that should be leveraged; prototype software
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an expanded coherent and exascale-ready software stack featuring breakthrough research advances that meets the needs of complex parallel applications and the requirements of heterogeneous exascale architectures
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is suitable for industrially scalable dry electrode processing. The successful candidate will play a central role in engineering fibrillar composite architectures that mimic PTFE performance while
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Higgs and Standard Model measurements, and searches for new physics and performance studies. Candidates with experience in modern AI/ML methods—such as transformer architectures, tokenization strategies
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contract Category (A,B or C) : A Contract/project period : Expected date of employment : March/April 2026 Proportion of work : 100% Desired level of education : PhD (Doctorate