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Field
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-cell and spatial-omics research. The ideal fellow will be interested in developing and applying novel computational algorithms to novel datasets generated in the setting of non-neoplastic and neoplastic
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to facilitate perceptual learning of different stimulation patterns; and (iii) the development of advanced AI algorithms capable of converting camera input into real-time electrical stimulation parameters. In
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patterns may mimic those observed in irrigated croplands. Key Responsibilities: Conduct research to develop algorithms and methodologies for mapping irrigation patterns using satellite imagery. Investigate
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to develop algorithms and methodologies for mapping irrigation patterns using satellite imagery. Investigate methods for detecting the timing and frequency of irrigation events from time-series remote sensing
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Regularization. We aim to develop mathematical understanding of implicit regularisation properties in deep neural networks to guide the development of algorithmic paradigms aimed at combining statistical
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robots. The role will involve developing advanced navigation systems. ESSENTIAL REQUIREMENTS PhD in Robotics, Software Engineering or similar disciplines Strong expertise in the localization and mapping
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the following area: The more details can be kindly found as below: Industrial AI Algorithm and Autonomous Decision-Making Systems RESPONSIBILITIES Research and develop autonomous decision-making algorithms
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The role will engage in cutting-edge translational research that develops computational models for assessing cardiac biomechanics and for predicting outcomes in cardiac diseases. This includes (1) a
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. SILEX 2025) to calculate the Fire Radiative Power (FRP) and compare with satellite observations (VIIRS, SLSTR, FCI). Develop a fire front segmentation algorithm using machine learning techniques (deep
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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will