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for wearable sensors that facilitate treatment of patients in a controlled clinical environment. The project will achieve this through exploring supporting the data management plan (WP1), and design iteration
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transfer solutions for a wearable sensor system that facilitates treatment of patients in a controlled clinical environment. The project will achieve this through exploring supporting verification and design
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neuroimaging methods to better detect disrupted function following neonatal brain injury, and identify new more energy efficient learning algorithms that could reduce the economic and environmental cost of AI
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neuroimaging methods to better detect disrupted function following neonatal brain injury, and identify new more energy efficient learning algorithms that could reduce the economic and environmental cost of AI
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and rolling out a new Multi-Sensor Core Logger integrated core scanning lab in the School of Earth Sciences. Opportunities will exist for fieldwork in Ireland and overseas. UCD Post doctoral Research
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models, and sensor configuration (with the support of the MIMRAD5D project partners) for the capture of a significant automotive perception dataset, the maintenance of the dataset, and to develop
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high performance computing sessions. These data may come from the video-capture, instrumentation of devices, and biometric sensors obtaining psychophysiological measurements like the electrical impulses
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: Reviewing existing quantum algorithms relevant to fluid dynamics and atmospheric modeling. Evaluating their compatibility with the structure and requirements of current NWP models. Identifying potential
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imaging algorithm in Hypoxic Ischaemic Encephalopathy). The Sophie project aims to develop a Neonatal MRI Biomarker for newborns with Hypoxic Ischaemic encephalopathy that is predictive of altered brain
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multimodal imaging techniques, such as computer vision and hyperspectral imaging, alongside Internet of Things (IoT) sensors that monitor critical parameters like temperature, humidity, and food quality in