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Field
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Postdoctoral Associate to investigate the neural mechanisms underlying continual learning in humans. The successful candidate will develop computational models examining the tradeoff between task
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will apply state-of-the-art machine learning algorithms and custom disease-relevant genomic datasets (e.g., coronary artery single-nucleus chromatin accessibility and RNA sequencing) to develop targeted
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. The Postdoctoral Associate will apply his/her technical skills toward development and implementation of machine learning, computer vision, and other algorithms for analysis of medical images and prognostication as
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geometric understanding of training in deep neural networks. The position offers excellent training opportunities at the intersection of machine learning and applied mathematics. Qualifications: - Applicants
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). The position requires engagement in pioneering research at the crossroads of machine learning and accelerator physics, aimed at improving the performance and capabilities of our light source facility. Modern
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engagement in pioneering research at the crossroads of machine learning and accelerator physics, aimed at improving the performance and capabilities of our light source facility. Modern complex accelerators
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) at the University of Florida (UF) is seeking a highly motivated and ambitious Postdoctoral Researcher with a strong background in Artificial Intelligence and Machine Learning (AI/ML). This is an exciting opportunity
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, algorithms or/and machine learning, through publications or conferences. - Strong communication skills. Overtime Status Exempt: Not eligible for overtime Appointment Type Restricted Additional Information
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members with careers that leverage the skills and unique experience they gained while serving our country, learn more at BNL | Opportunities for Veterans at Brookhaven National Laboratory . Equal
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and great opportunity of interdisciplinary training in machine learning and functional genomics. The project combines cutting-edge computational approaches, especially state-of-the-art machine learning