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Field
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Approximation. Parameterized Complexity is a vastly growing area within theoretical computer science that allows for the development of exact and approximation algorithms for computationally hard problems by
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Professor Daniel Paulusma from Durham University and Professor Vadim Lozin from the University of Warwick. The general aim of the project is to develop algorithmic meta-classifications, which state that any
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courses related to AI/ML, programming languages, data structures and algorithms, operating systems, network security, visualization, and human-computer interaction, as well as participate in the full range
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Vadim Lozin from the University of Warwick. The general aim of the project is to develop algorithmic meta-classifications, which state that any computationally hard graph problem satisfying some condition
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programme in probabilistic AI. The hub will develop the next generation of mathematically principled, scalable and uncertainty-aware AI algorithms. This will be achieved through: bringing together world
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. Expected outcomes include: development of novel algorithms that significantly improve predictive accuracy for equipment failure; creation of scalable monitoring systems that reduce operational costs
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About us: We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with
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Manager will work with the Directors of the Leverhulme Centre for Algorithmic Life and key strategic partners to develop and implement a strategy and plan of activity for cross-sector engagement and
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photogrammetry algorithms for accurately measuring labware alignments and heights in the carriage. Integrating the developed vision system into labware automation system to enable individual labware identification
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courses: Spatio-Temporal Data Mining and Big Data Analytics, launched in 2014 and still growing and developing in reputation; and Geospatial Sciences (GIS & Computing, BIM, Hydrographic Surveying