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Field
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We are seeking a postdoc to co-design efficient and realistic simulation algorithms for noisy quantum circuits in superconducting hardware, combining quantum modeling with hardware-aware performance
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that developed solutions are not only innovative but also scalable and implementable in field scenarios. By integrating both software and hardware considerations, this project aims to advance the state-of-the-art
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simulating/implementing quantum algorithms for field theories on quantum hardware. Appointment Detail: This post‑doctoral position is a full‑time, 12‑month appointment with annual renewal contingent
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interface of hardware and software for world-leading observatories, and collaborate with international teams of scientists and engineers – then welcome to the team! Our ground-based astronomical
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, tape-out, and testing, preferably with applications to AI systems ● Design, analysis, and modeling of AI hardware such as deep neural network accelerators or neuromorphic computing. ● Emerging AI
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hardware and embedded security, confidential computing, trusted execution, secure AI, and related areas. This post is suitable for candidates with a wide range backgrounds relevant to cyber security
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ligand libraries, bioinformatics analysis workflows, and hardware and software support. The incumbent works closely with the BSBC Director and interacts routinely with UNMC investigators and other
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selection and switching in real time Integrate surrogate models with physics-based solvers, e.g. SOFA, FEniCSx, SOniCS, and clinical or phantom data Deploy models on ARSPECTRA hardware, including optimisation
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, tape-out, and testing, preferably with applications to AI systems ● Design, analysis, and modeling of AI hardware such as deep neural network accelerators or neuromorphic computing. ● Emerging AI
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-of-the-art data management, machine learning and statistics techniques. With the advancement of Exascale systems and the variety of novel AI hardware designed to accelerate both training and inference