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). In parallel, we developed computational methods for the analysis of spatial omics data (Bortolomeazzi Nature Comms 2022) and clustering of rare cell populations (Martens, Bioinformatics 2023). About
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and of research methods and techniques to work within established research programmes. Applicants should be able to demonstrate a successful track record in clinically-relevant psychological research
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and clinical neuroscience. This project involves development of machine learning methods for mapping the relationships between diffusion MRI (dMRI) and phase-sensitive OCT (PS-OCT) in the same tissue
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resolution, longitudinal, technical and social data with the aim to better understand energy use. The programme is an interdisciplinary collaboration between the School of Geography and the Environment (Oxford
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and social data with the aim to better understand energy use. The programme is an interdisciplinary collaboration between the School of Geography and the Environment (Oxford), the Department
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, publishing results, and presenting findings at conferences. This role may involve superconducting microwave circuit design and simulation, theoretical analysis of classical and quantum circuits, numerical
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the model, its numerical implementation in a finite element code, and its validation against experimental data in collaboration with experimental collaborators. You will also engage with the hub activities
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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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, such as the internet of things (IoT) and cyber-physical systems (CPS). These systems require scalable and efficient learning methods that can function under limited communication, computation, and energy
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-year postdoctoral research position in stellar astrophysics, with a focus on computational magnetohydrodynamics (MHD). This position is funded by an STFC Small Award and will be supervised by Professor