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will design and implement novel computer vision and machine learning methods for “sensorized” cameras that extract medically relevant features without transmitting raw video. You will evaluate algorithms
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project is to develop a high-performance computing framework for mass spectrometry proteomics to enhance efficient processing and interpretation of large datasets using deep learning algorithms and GPU
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that are of practical interest. The postdoctoral researcher will contribute to the theoretical foundations of inverse problems involving wave phenomena, develop cutting-edge computational algorithms, and apply
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developed by the project partners will be based on two key technologies: machine learning algorithms that generate artificial yet realistic data points (synthetic health data) and secure multi-party
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particle (SEP) events. The project is a joint collaboration of Algorithmics and Computational Intelligence research group at the Department of Computing and Space Research Laboratory at the Department