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using a variety of advanced methods with the support of project supervisors. The postholder will have completed a PhD in a relevant discipline and have expertise in quantitative research methods
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to have the following skills and experience: Essential criteria PhD qualified in relevant subject area Extensive experience working in bioinformatics with large datasets Previous experience in statistical
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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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this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD qualified in relevant subject area Extensive experience working in bioinformatics with large
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develops new intellectual understanding Disseminate research findings for publication, research seminars etc Supervise students on research related work and provide guidance to PhD students where appropriate
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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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. The successful applicant will use state of the art inference algorithms to design, use and share the findings of epidemiological models that integrate across large and diverse datasets including capture-mark
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progression once in post to £48,149 Grade: 7 Full Time, Fixed Term contract up to March 2028 Closing date: 13th August 2025 Background This research project aims to establish the theoretical and algorithmic
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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
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conditions. Our work combines traditional statistical methods with advanced artificial intelligence algorithms to identify patterns in disease. We also use qualitative methods to understand lived experiences