29 high-performance-quantum-computing Postdoctoral positions at University of Cambridge
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candidate should have (or expect to soon be awarded) a PhD in quantum information theory (including some aspects of quantum computing, quantum cryptography and/or quantum communication) and some experience in
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"Coupled Magnetic Hybrids for Advanced Quantum Technologies", a collaboration with the City University of Hong Kong (CUHK). The aim of the role is to explore how nanomagnetic elements in proximity structures
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to develop and improve current simulation methods (quantum and classical) to study such systems. The overarching aim of the post-doctoral position is to develop and apply computational approaches that enable
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the starting date is negotiable. The current funding is guaranteed from the Montague Burton Fund. We are looking for a candidate who is a health economist with excellent computational skills. The post is
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research centre well-known for its close-knit community, friendly atmosphere, and outstanding research support. We are seeking a post-doctoral research associate with experience in computational approaches
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Lab's expertise in tumour initiation and early transformation, this project aims to intercept breast cancer before it starts, with a particular focus on individuals carrying high-risk mutations in BRCA1
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connectome, with a focus on the chemosensory circuits involved in human host-seeking. The principal focus will be on the high level proofreading, annotation and analysis of connectomics data. This will include
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machine learning tools and working on Linux High-Performance Computing platforms would be highly desirable. This is a highly collaborative role and you will work with scientists and clinicians from other
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experimental medicine studies focusing on energy homeostasis and glucose/lipid homeostasis Data Collection & Analysis: Perform in vivo metabolic testing, blood sample and tissue analyses, and molecular biology
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-generation AI hardware (ASIC) accelerators. The UK's Advanced Research Invention Agency (ARIA) is supporting an ambitious programme of work that aims to reduce the the cost of AI by more than 1000x: https