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hold an MSc in Earth science, environmental science, data science, physics, mathematics or computer science, with practical machine learning/artificial intelligence courses and relevant project and
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individuals and patients. These projects involve large-scale neuroimaging data collection at 3T and 7T, computational modeling of brain responses using machine learning methods, and cross-institutional clinical
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participant outcomes. The project will use a variety of approaches, including human perceptual experiments, machine learning, digital signal processing, and computational models of hearing. UConn has a vibrant
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, technical depth, and a strong track record of applied research in Computational Biology, Structural Biology, Protein Engineering, Machine Learning, or a closely related field. Strong understanding and
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diffraction data where the information extends towards 3-d space. Machine learning offers promising approaches for the solution of complex problems of disorder, ultimately aiming at general and automated
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deploy machine learning and deep learning models (transformers, large language models) for immunological data (biological sequences, single-cell data, and protein structures, virtual drug screening) Use
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Adaptive Learning in Brain-Robot Interactions School of Electrical and Electronic Engineering PhD Research Project Self Funded Dr Mahnaz Arvaneh Application Deadline: Applications accepted all year
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within SCI and across other departments within Pitt, and initiatives like the $11.6M Western Pennsylvania Quantum Information Core (https://www.pitt.edu/pittwire/features-articles/pitt-investment-pa
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knowledge of power system security and machine learning being crucial. The Associate will primarily work alongside National Grid engineers to integrate the machine learning backend of the intrusion detection
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science/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning