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Field
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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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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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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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, 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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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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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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United Kingdom Application Deadline 17 Sep 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
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development. The main tasks will be in photometric light curve analysis and validation (Gaia and PLATO) and data analysis and development of novel scientific algorithms and applications in the areas
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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