38 distributed-algorithm "University of Exeter" Postdoctoral positions in United Kingdom
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award at FOCS 2019. These positions are supported by an ERC Advanced Grant (Distributed Quantum Advantage , 2026–2031) and a QuantERA grant (Quantum Network Algorithms , 2026–2029); in the QuantERA
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of the elderly to space robotics. We are now looking for a postdoctoral researcher in quantum algorithms and optimization for Life Science applications. Are you as excited about quantum technology and its future
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reference ID 1215). About Us Transform Your Career and Help Shape a Greener, Healthier, and Fairer Future Join the University of Exeter, a top 200 Russel Group university (QS & THE World University Rankings
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Experimental Governance”, joining a team led by Rob Smith at the University of Edinburgh, and Sarah Hartley at the University of Exeter. This exciting project is funded by ARIA, the UK’s Advanced Research and
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. The Opportunity: We are seeking to appoint a talented researcher to the role of Postdoctoral Research Associate (PDRA) to work on The Leverhulme Centre for Algorithmic Life (LCAL). LCAL is a major new
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Assistant (RA) or a Postdoctoral Research Associate (PDRA). The appointed candidates will support advanced research initiatives focusing on systems design, distributed systems, and algorithmic optimization
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concepts underlying the GIG into efficient data structures and algorithms. Your work will also involve developing algorithms to manipulate and analyse GIGs, creating efficient methods for translating GIGs
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on the mathematical theory of deep learning as part of the joint NSF-EPSRC project “DMS-EPSRC: Asymptotic Analysis of Online Training Algorithms in Machine Learning: Recurrent, Graphical, and Deep Neural Networks
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advance the fundamental science of artificial intelligence and address some of the field's most important challenges. You will be responsible for researching and developing novel algorithms and techniques
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NSF-EPSRC project “DMS-EPSRC: Asymptotic Analysis of Online Training Algorithms in Machine Learning: Recurrent, Graphical, and Deep Neural Networks”. The research will involve collaboration with