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. The ideal candidate will possess not only a deep conceptual understanding of neuroscience but also advanced technical expertise in machine learning, artificial intelligence, and data modeling approaches. We
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for highly motivated postdoctoral candidates with a PhD in bioengineering deep knowledge in computational biology and machine learning. Candidates with a molecular biology or engineering degrees with
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monitoring systems, bedside monitoring devices, or medical device data. Experience linking physiologic waveform features to clinical outcomes. Experience with machine learning, deep learning, predictive
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field Demonstrated expertise in one or more of the following areas: Machine/deep learning, artificial intelligence, statistical modeling, or computational modeling Human neuroimaging analysis, including
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) conferred by start date Demonstrated experience with imaging and/or video datasets Training and experience in machine learning, computer vision, and deep learning methods Excellent English language
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Medicine are seeking to appoint a Postdoctoral Research Fellow to join a project developing and validating deep learning computer vision models to classify mosquito breeding habitat on very high-resolution
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. The fellow will also work closely with SCEC Senior Machine Learning Engineer Dr. Lauren Klein Dubin, who will provide day-to-day supervision of the fellow's technical work. The fellow will have opportunities
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imaging, genetics, omics, EHR data, and clinical outcomes. Ongoing work builds on deep-learning phenotypes from cardiovascular imaging at population scale and extends toward myocardial tissue remodeling
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research at an unprecedented scale. ROAR empowers educators, families, clinicians, and researchers with research-backed assessments to advance learning, accelerate research on learning differences, and
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QUALIFICATIONS: PhD in computer science, electrical/biomedical engineering, statistics, applied mathematics, or a related field. Strong track record in machine learning/deep learning with imaging data