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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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real-time, and will be tested and demonstrated on a state-of-the-art HiL rig and an autonomous test vehicle. The post is focused on the development of automotive-grade algorithms and estimators that will
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real-time, and will be tested and demonstrated on a state-of-the-art HiL rig and an autonomous test vehicle. The post is focused on the development of automotive-grade algorithms and estimators that will
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. This interdisciplinary collaboration with the University of Lincoln and University of Liverpool focuses on developing innovative computational approaches that integrate advanced genomic analysis with state-of-the-art
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. This interdisciplinary collaboration with the University of Lincoln and University of Liverpool focuses on developing innovative computational approaches that integrate advanced genomic analysis with state-of-the-art
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. We have an exciting opportunity for an enthusiastic and motivated postdoctoral Computational Biologist to contribute to multimodal data integration as part of a translational genomics programme within
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opportunity for an enthusiastic and motivated postdoctoral Computational Biologist to contribute to multimodal data integration as part of a translational genomics programme within the group led by Professor
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once in post to £48,149 Grade: 7 Full Time, Fixed Term contract up to August 2028 Closing date: 25th July 2025 Background We are seeking an innovative Research Fellow in Computational Metabolomics
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based at the School of Electronics and Computer Science, Southampton. The project is researching, developing and evaluating decentralised algorithms, meta-information data structures and indexing
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algorithmic foundations of quantum adversarial machine learning, an emerging field at the intersection of quantum computing and machine learning. It investigates how the unique capabilities of quantum computing