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Field
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data analysis and modelling on this project. Specifically, advanced imaging processing skills, which will allow them to develop and validate algorithms for combination of multiparametric / multi-scale
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for the discovery of new physics experiments) Developing, benchmarking and advancing state-of-the-art AI-driven exploration, optimization, and search algorithms in extremely complex and enormously large spaces
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focuses on combining novel genome engineering tools (e.g., CRISPR-based) and computational algorithms to enable regenerative cell therapies. Now, we are seeking a highly driven postdoctoral researcher
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algorithmic graph theory. The purpose of the role is to contribute to the project "Algorithmic meta-classifications for graph containment", working with Professor Matthew Johnson, Dr Barnaby Martin and
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teams to contribute to the development of fundamental aspects of computer science (models, languages, methods, algorithms) and to develop synergy between the conceptual, technological and societal
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: Design, implementation and testing of new methods and algorithms so that SIESTA can harness the compute power of the latest generation of (pre-)exascale architectures and tackle novel scientific challenges
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strong overlap in the fields of topological quantum field theory, quantum condensed matter theory, and quantum computing and algorithms. Qualifications Applicants must hold a PhD in physics or a related
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The Role Applications are invited for a Postdoctoral Research Associate in Computer Science with a particular emphasis on structural and algorithmic graph theory. The purpose of the role is to
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methods and tools for adaptive, AI-driven embedded algorithms to support real-time analytics and decision-making in IoT, wireless communication, and remote sensing systems Collaborate with multidisciplinary
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together experts in systems neuroscience, AI, and engineering. This ambitious initiative promises to offer unprecedented insights into the brain's algorithms of perception and cognition while serving as a