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Field
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% Superannuation (Academic Level A) Based at our St Lucia Campus About This Opportunity Work with the Stehbens Group at AIBN, to conduct molecular, biochemical and live-cell imaging experiments of cell culture
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flying on top of thunderclouds in the Gulf of Mexico and is currently scheduled for summer 2028. Through this project, our group is building an innovative airborne gamma-ray imager, capable of localizing
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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI
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to the POSSEM trial, using photon-counting coronary CT angiography, advanced imaging, and computational modelling to identify patients at risk of accelerated coronary artery disease and enable more personalised
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external emails. We are seeking to recruit a Bioinformatician, for an initial period of 18 months, funded by an ARPA-H LIGHT (lymphatic imaging, genomics, and phenotyping technologies) grant, a multicenter
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learning/computer vision methodology. The focus of this project will be on the development of deep learning methodology for spatio-temporal medical image analysis, that is medical images that evolve over
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measurements: transepithelial resistance, muscle contraction Inflammation level measurements: RT-qPCR, ELISA, bioplex Immunocytochemistry, imaging and 3D reconstruction Flow cyrtometry Single-cell transcriptomic
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implementation of elastomer adhesives Optimization of formulation for 3D printing and 2D printing Contribute to ongoing ionic liquid formation projects Design and prototype and scalable processing Collaborate with
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, including design approaches, scanning methods, signal processing techniques, and comparison with alternative detection technologies. ii. Support design and development of NQR prototype, including system
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reconstruction, processing, synthesis, and registration, as well as AI for treatment outcome prediction and clinical decision making. The projects will involve using multi-modality images (CT, CBCT, MRI, PET