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-fidelity finite element models to investigate surface wave propagation in soft biological tissues, forming the foundation for subsequent statistical and machine learning frameworks that integrate
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. Candidates are expected to have experience in one or more of the following areas, such as: wireless networks/communications, machine learning/vision, intelligent transportation systems, intelligent sensing
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to support real-time response to Emergency Events such as Wildfires. Platforms include Satellite, Aircraft, Drones, Mobile Devices using Optical, LiDAR, Navigation sensors. Highly automated Machine Learning
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(piezoelectric micro-machined ultrasonic technologies) for biomedical imaging is highly desirable. The appointee will have a strong track record of delivering innovative research outcomes at the cutting edge
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technologies including VR, audio or image processing, machine learning and AI, computer vision, and robotics. The successful candidates will play key roles in the development and enhancement of a European
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every colleague is valued and empowered to thrive. Our dedication to these values ensures that we foster a culture of mutual respect, open collaboration, continuous learning, and innovative thinking. Join
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valued and empowered to thrive. Our dedication to these values ensures that we foster a culture of mutual respect, open collaboration, continuous learning, and innovative thinking. Join us at RCSI, where
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, and machine-learning approaches to astrophysical problems. The post-holder will work with other academic staff, researchers, and students in the lively, collaborative, and international research
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. Quantitative, computational, or mixed-method approaches are particularly encouraged, including but not limited to geospatial analysis, machine learning, predictive modelling, and causal inference techniques
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with carrying out original research to develop new machine learning approaches to link different scale geochemical-mineralogical-petrophysical datasets within a 4D geological framework. An initial focus