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Project title Multi-Modal Large Language Model for Medical Image Analysis Research period 2 years Abstract The proposed research project aims to develop a novel multi-modal large language model (MLLM
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. Particular emphasis to be placed on developing and applying emergent system identification and modal decomposition techniques as well as statistical analysis of large datasets. Candidate will disseminate
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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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, visible, and ultraviolet; acoustic; radio spectrum; magnetic field strength; charged particle count; and environmental sensors. The project aims to conduct an exhaustive, long-term, multi-modal aerial
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the sensory coding of orofacial thermal, Chem esthetic, and taste sensations, and cross-modal and multisensory interactions between somatosensory and gustatory signals in the periphery and brain. The Lab’s work
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sharing clinical data from neurodegenerative disease cohorts. You will be responsible for: Technically contribute and coordinate the development and implementation of data systems and analysis platforms
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-modality ultrasound analysis. The appointee will be part of the Noble research group at the Institute of Biomedical Engineering, based at the Old Road Campus in Headington. The post is funded by UKRI and is
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of treatments. The role of trace elements can be measured with Scanning Transmission X-ray Microscopy, integrated into a multi-modal imaging platform: using also super-resolution Infrared microscopies, X-ray
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and to users Validating predictive models in close collaboration with clinical partners, and interfacing image-based models with other modalities Writing and presenting scientific work at top
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processes, Bayesian inference, signal models, sampling theory, sensing techniques, optimisation theory and algorithms, multi-modal data processing, high-performance computing, mathematical image analysis