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computing, domain-specific multi- and manycore architectures, networks-on-chip (NoCs), methods and algorithms for application parallelization, simulators and virtual platforms for application- and
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, charities, as well as other universities and research institutes across the UK and internationally. The overall programme of research will be jointly developed by Prof. Nophar Geifman and the person appointed
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(e.g., based on physiological signals or direct inputs from occupants) and developing algorithms, including machine learning methods. The work will include statistical modelling, data-driven modelling
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are searching for a motivated PhD candidate to design practical over-the-air computing algorithms and protocols for future edge AI applications. About the employer The research of this PhD position will be
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postdoctoral position is available in the Geometric Machine Learning Group at Harvard University, led by Prof. Melanie Weber. This role offers an opportunity to perform research at the intersection of Geometry
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, artificial neural networks and bio-inspired robotics: "Rhythmic-reactive regulation for robotic locomotion" (Supervisor: Prof Fulvio Forni) will apply techniques from nonlinear control and optimisation
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The Computational Turbulent Reacting Flow Laboratory, led by Prof. Michael E. Mueller, invites applications for postdoctoral or more senior research positions in the field of atmospheric aerosol
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learning and generative AI approaches, creating synthetic virtual patient cohorts from multimodal datasets. Your work will involve designing advanced algorithms and high-throughput workflows for crafting
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deep learning and generative AI approaches, creating synthetic virtual patient cohorts from multimodal datasets. Your work will involve designing advanced algorithms and high-throughput workflows
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terrestrial system models, for example using data analysis methods, such as data assimilation, physical- or process-based machine learning, or deep learning algorithms Analysis of the effects of human