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Job Description Position Details School of Computer Science Location: University of Birmingham, Edgbaston, Birmingham UK Full time starting salary is normally in the range £36,636 to £46,049 with
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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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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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. There are opportunities to broaden out into other areas such as new algorithm development, and advanced computational methodologies for integrated analyses. You will have a key role in planning, designing and executing a
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Position Details School of Computer Science Location: University of Birmingham, Edgbaston, Birmingham UK Full time starting salary is normally in the range £36,130 to £45,413 with potential
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datasets Previous experience in statistical analysis of data, leading to peer reviewed papers and/or presentation of findings at conferences Evidence of excellent scientific analysis skills Strong computer
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river system Develop, test and apply algorithms for the processing and analysis of satellite data drawing on the latest physics-based and/or data-driven techniques Contribute to work on the automation and
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. There are opportunities to broaden out into other areas such as new algorithm development, and advanced computational methodologies for integrated analyses. You will have a key role in planning, designing and executing a
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treatment and reducing brain injuries Modern MRI scans tell us about a tumour’s biology. Through advanced computing (radiomics), it is possible to extract much more information from MRI images than is visible
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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