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teaching faculty in Computer Vision and Image Processing to lead the course, "Machines that see," which introduces students to core computer vision concepts, a vital area of AI. This role involves delivering
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more complete picture of how processing speed is related to health outcomes. The candidate will work in a multidisciplinary environment consisting of PhD-level scientists, graduate students and
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to recruit a research assistant to develop AI-enabled healthcare applications. Key Responsibilities: Develop and fine-tune computer-vision models, instance segmentation, and retrieval-based estimation from
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brain health. This project combines MRI and EEG/MEG studies with behavioral, genetic, and clinical measures to yield a more complete picture of how processing speed is related to health outcomes
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models related to modern data management challenges (e.g., query feasibility, data correlations, probabilistic evaluation, scalability). Prototype and evaluate data system components or extensions
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computational biophysics Machine learning and data analysis for biological systems Biomedical imaging and signal processing Molecular modeling and simulations AI applications in bioinformatics or health sciences
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exploring new modes of human-computer interactions. Has demonstrated experience in exhibiting works and/or presenting at festivals and conferences, with the ability to teach and support students in developing
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records and medical images, for applications pertaining to patient diagnostics and prognostics. We are seeking a Postdoctoral Researcher to join the team and make significant contributions to the field
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and medical images, for applications pertaining to patient diagnostics and prognostics. We are seeking a Research Assistant to join the team and make significant contributions to the field
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AI systems capable of generating data such as text, images, sounds, graphs and other data types. Students will explore the core principles behind generative models, including advanced transformer