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Field
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learning tools for the prediction of composite manufacturing processes. You will work on development of algorithms, custom written codes, application of commercial finite element software and development
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-Making and Route Optimisation: Develop adaptive algorithms within a bias-aware ensemble Kalman filter framework to propose alternative flight paths dynamically. The system will aim to maximise safety and
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Zero transport strategy. Outcomes will include novel AI algorithms, validated navigation architectures, and new insights into next-generation intelligent mobility solutions. The student will undertake
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visual inspection. The research will address several challenges: Complex Surfaces: Developing robust algorithms (leveraging Convolutional Neural Networks and Transformers) capable of identifying tiny
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work with hands-on offloading algorithm design and development for IoT networks. The core responsibility is to build and validate edge-assisted offloading strategies, complete with software APIs, through
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pre-processing), mining dictionary data, and developing novel algorithms for time-sensitive word sense disambiguation (WSD) in Latin, contributing to the creation of a 100-million-token annotated corpus
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conduct cutting-edge research on topics including, but not limited to: Complexity theory Quantum algorithms and complexity Sublinear algorithms Interactive proofs, PCPs, and zero-knowledge proofs
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algorithms based on neural activity data (local field potentials, LFPs) from key deep brain stimulation targets including the basal ganglia and thalamus. Auxiliary data available to implanted devices include
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develop a feedback interface integrating human natural sensory and robot’s artificial information. This will encompass mechatronics design, system integration, robotic control, computer vision algorithms
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. Analysis of images will investigate the efficacy of manual digital approaches (e.g., Dot Dot Goose) and the development of a marine litter characterisation and quantification algorithm for automated analysis