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to begin on or after August 1, 2024. The position will focus on Ab Initio Molecular Dynamics (AIMD) to study polymer electrolytes, with a special interest in machine learning accelerated methods
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team player and collaborator. Experience in any of the following is a huge plus: hypothesis testing followed along with appropriate statistical analysis methods, machine learning, programming, control
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receive mentorship and resources to prepare them for an independent career, including advanced training in research methods like fMRI, machine learning, network science, and psychometric analysis. They also
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2024. This role is centered on cutting-edge research at the nexus of machine learning, deep learning, computer vision, psychology, and biology, with foci on psychology-inspired AI and addressing
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. This position is available immediately. Duties and Responsibilities: Develop machine learning models to identify relevant signals from audio and text data from clinical sessions Develop and evaluate interactions
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, and affective neuroscience (functional MRI and psychophysiology) with advanced analytic methods (e.g. machine learning and structural equation modeling). The research associate will be working on funded
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learning networks and other machine learning techniques (artificial neural networks, classification and regression trees, random forests, etc.). Experience working with pollutant dispersion models such as
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of the Pennsylvania Rural Health Model; and Examining Drivers of Differences in Measures of Cancer Treatment within the Military Health System. The successful applicant will join a vibrant team of scholars and benefit
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and managing research inquiry. Have experience writing and preparing scholarly manuscripts. Demonstrate competency in oral and written communication. Have computer skills including experience with
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cigarette smokers, implementation of longitudinal analyses, machine learning for outcome prediction, and integration of multimodal neuroimaging data. Candidates will be expected to contribute to ongoing data