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the ranking. However, STV method becomes considerably more complex with encrypted ballots. Our goal is to develop an algorithm/protocol to count encrypted ballot using the STV method. Our first point of
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this, the Fellow will implement a universal design methodology for such fluids of complex rheology, using a Machine Learning (ML) algorithm to be incorporated in a Computational Fluid Dynamics framework. Training
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objects, by embedding them into a 2 or 3-dimensional space through a representation learning algorithm, has been widely used for data exploratory analysis. It is particularly popular in areas such as
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can feed directly into precision surgery algorithms and clinical trials. Few PhD projects offer such a clear line of sight from variant to mechanism to clinical translation. Located on the thriving
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of the position is to pursue cutting-edge research in automata theory, and possibly at the interface with algorithms (fine-grained complexity). We will consider applications for employment on a part-time or other
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learning algorithms and specific applications in GeoAI In-depth knowledge of spatial/GIS programming, preferably in Python A proven track record of application of machine learning to real-world problems
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-world systems. While most of the work will be computational or mathematical, you will also have the opportunity to visit BASF in Ludwigshafen, Germany for three months to try out the new algorithms in
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An exciting opportunity has arisen for a talented computer scientist to join our team as a researcher within the Green Algorithms Initiative in the Department of Public Health and Primary Care, one
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novel multi-objective optimisation algorithms, to evaluate metrics such as material circularity, system efficiency, cost, and carbon footprint. The University of Surrey is ranked 12th in the UK in
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algorithms. Project title: Multimodal AI for Immunology Applicants are invited for the post of PDRA in Multimodal AI for Immunology. The post-holder will develop multimodal deep learning models to predict