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Field
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and innovation catalyst, in this exciting project, you will develop novel algorithms to monitor and analyse workers' movements, detect harmful movement patterns, and implement simple intervention
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and interoperability, and efficient processing and management of time-series datasets and metadata originating from IoT sources (such as environment sensors and meters) closer to the data provider
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and simple embedding alignment to develop architectures that can process and reason across modalities (vision, language, audio, sensor data) from the ground up. How do we build a truly unified
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research tasks investigating navigation and integrity assessment of several aircraft-related sensor modalities. The candidate will be mentored by Dr. Jay Wilhelm (Associate Professor of Mechanical
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of fingers, the shapes of the fingers, and the positions of tactile sensors), and the control policy for that hand, when given a particular task or set of tasks. Through this, we aim to develop a framework
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(CPS) for aquaculture, to sensors and platforms for maritime applications. The Postdoc’s primary task will be to lead the development of algorithm, software, and hardware to extend the current HAUCS
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specialist collaborator to guarantee adequate integration of perception and action; advanced motion-planning and control algorithms, continuously refined via robotic digital twins, enable reliable handling
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us to build/learn generative, probabilistic forward models of users and their physical and computational environments. This will involve modelling sensors, developing dynamic models for control and
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a breakthrough concept to upgrade existing fiber optic networks to acoustic sensor arrays, becoming a key component for managing smart cities. Except for a few applications, DAS data are typically
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algorithms for dynamic structured data, with a particular focus on time sequences of graphs, graph signals, and time sequences on groups and manifolds. Special emphasis will be placed on non-parametric