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neurosurgical centre. In this role the successful candidate will develop deep learning algorithms and validate models on diverse clinical data which include magnetic resonance imaging (MRI) and computed
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mathematical, algorithmic and computational communities, employing foundational tools to break new ground in AI, and redefine its future use to benefit science, industry, the economy and society. The Hub
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This research project aims to establish the theoretical and algorithmic foundations of quantum adversarial machine learning, an emerging field at the intersection of quantum computing and machine learning. It
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Term Division/Team: Department of Computer Science Hours Per Week: Full Time (1 FTE) Closing date (DD/MM/YYYY): 20/08/2025 Contract Duration: 36 months School/Directorate: School of Engineering We
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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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, transcriptomics (bulk, scRNAseq) epigenetic profiling (methylome, Atac-Seq, Chip-seq) and proteomics, using computational methods. Algorithm Development: Designing and implementing algorithms to process, analyse
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modelling, advanced AI algorithms, and decision-support tool development for various hydrogen technologies-based energy systems. Responsibilities will include programming, analysing and interpreting data, and
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university/spinout environment. This is a unique opportunity to work at the forefront of applied research and innovation, helping translate novel control algorithms and hardware prototypes into real-world
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contribute to the design and implementation of state-of-the-art machine learning models for medical applications. Responsibilities include developing and evaluating algorithms in Python, applying large
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of Oxford. The post is funded by the National Institute for Health and Care Research (NIHR) and is fixed term for 24 months. The researcher will develop multi-sensor 3D reconstruction algorithms to fuse