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Field
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goals As a researcher in this project, you will work on mathematical models for describing the radio environment and to design algorithms for estimating, for example, the location and spectral
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We invite applications for a full-time Postdoctoral Research Associate to join the new Data-Driven Algorithms for Data Acquisition (DataAcq) project. This is a timely project developing new
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of novel algorithms to analyse short tandem repeats from short- and long-read sequencing data. Knowledge of current analytic approaches for obtaining insight into the aetiology of mendelian and complex
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candidates whose work lies at the intersection of statistics, machine learning, data analytics and modern AI algorithms. This includes, in particular, statistics for high-dimensional and complex data
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. These problems have been compounded by the emergence of Artificial Intelligence. New forms of algorithmic manipulation have been used to sow discord in democratic societies, undermine trust in politics, and erode
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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
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uses, improving the AI and MRI algorithms, and linking them with information from biological studies on tumour tissue. This project harnesses AI to improve diagnosis and clinical decision-making leading
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Job Purpose To make a leading contribution to the development of innovative muon tracking algorithms for cutting-edge applied nuclear physics research. The successful candidate will be expected
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algorithms proficiency in both general-purpose programming (e.g., Python) and scientific computing, with a preference for experience in Julia Experience in writing up research work for publication Highly
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collegiality is at the heart of what we do. The Department’s research structure consists of five Research Groups: Algorithms and Complexity (ACiD) Artificial Intelligence and Human Systems (AIHS) Network