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Field
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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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variants of importance sampling. We will connect these methods to modern formulations of Monte Carlo algorithms to improve their accuracy, scalability, and overall computational cost. The methodology so
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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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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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contributing to our clinical NLP tools, algorithms and interfaces used by clinical specialists. The post holder will be expected to contribute to: Extend our software platforms for electronic healthcare record
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will be able to teach Discrete Mathematics, Design and Analysis of Algorithms, Models of Computation, and Algorithms and Data Structures. The exact courses tutored may vary but would likely consist of
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formulation, which displays striking similarities to that used by the Computational Fluid Dynamics (CFD) community, has inspired the investigators to adopt conventional CFD algorithms in the novel context
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apps and software algorithms would be desirable, as would an understanding of major depression and its pharmacological treatments. Diversity Committed to equality and valuing diversity Our active
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-resource settings. This project aims to achieve several objectives, including the development of a new AI-algorithm and a paired dataset for comparing how different imaging techniques influence
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quantitative analysis skills and experience developing algorithms and/or conducting statistical analyses with biological datasets. Background and work knowledge in statistics, algorithms, optimization of novel