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Assessment Models (IAMs) such as GCAM or PAGE. The candidate must have a PhD degree in a related field, be fluent in computer programming, preferably python, and will ideally have experience in working with
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University Department of Head and Neck Surgery & Communication Sciences The Duke Transdisciplinary Otolaryngology Research, Community Health and Equity (Duke TORCHE) Lab in the Department of Head and Neck
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examine how withdrawal changes the brain’s processing of painful stimuli in people with and without chronic pain, as well as its impact on their ability to abstain from smoking. The postdoctoral researcher
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. The research aims to: 1) Delineate the chemical speciation and mineral phases associations of these critical metals in AMD wastes; and 2) Evaluate the implications of these associations for extraction processes
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. Occupational Summary The Duke Neuroradiology Division specializes in CT fluoroscopy guided spine intervention procedures to treat pain as well as the diagnostic workup and treatment of patients with CSF leaks
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, excellent communication, data processing, organizational, written and oral presentation, and problem-solving skills. Experience in animal handling and/or high throughput sequencing analysis is strongly
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about new methods, is a plus. Strong programming skills in Python or R, and Linux Shell; experience in genomics data processing and open source repositories e.g. GitHub is a plus. Strong motivation and
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processes that are disrupted across a range of conditions, such as major depression and autism spectrum disorders. Qualifications: The candidate must have a Ph.D. in neuroscience or a related discipline using
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, including development of new computational tools for processing large-scale biospecimen data Creation of novel machine learning frameworks for automated scientific analysis and discovery Design and
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Computer Science and Electrical and Computer Engineering departments, and the School of Medicine. The group emphasizes collaborative and multidisciplinary work and brings together expertise from machine learning