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networks of these devices we will use digital twins; machine learning models trained to predict physical systems but are differentiable. This project will advance the machine learning methods, particularly
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EPSRC CASE Studentship. University of Sheffield and Syngenta Crop Protection Machine learning is increasingly used for decision making and molecular design in the pharmaceutical and crop protection
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We have an exciting role working with collaborators in Sheffield and at Ohio State University that combines ecology, machine learning, hardware and software development to solve a critical challenge
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materials using the framework of atomistic spin dynamics with coupled spin-lattice dynamics. To undertake this, we will first explore the use of machine learning to create models of the interactions between
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sensor data. Supervisor Bio Dr. Matthew Ellis’ research intersects machine learning and physics; looking to better integrate advances in both to create new paradigms for computing. With a background in
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meaningful features from these sensor data and apply machine learning algorithms to predict health outcomes; 2) to explore advanced deep learning methodologies to further exploit the information embedded
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PhD Scholarship: Real-Time Brain Injury Prediction and Protection Framework for Intelligent Vehicles
. The core objectives include: Based on existing car collision simulation and traffic accident database, using machine learning methods to establish the relationship between vehicle kinematics and occupant
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capability in natural language understanding and generation. Conversational systems or dialogue systems are useful in supporting interactive information exchanging, especially between human and machines
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(diachronic text analytics). Researchers in the network will encounter different theories of, and approaches to meaning (structuralist, relational, distributional, cognitive, encyclopaedic, social) and learn