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statistical and machine learning methods applied to large claims and electronic health record databases and multimodal data, including physiological waveforms and medical imaging. We foster a collaborative and
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position is supported by a National Institute on Drug Abuse-funded R01 award. The position involves contributing to a dynamic team engaged in developing and applying a combination of statistical analyses and
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Qualifications: A PhD, MD/PhD, or equivalent research doctoral degree in neuroscience, biomedical data science, computer science, psychology, psychiatry, statistics, engineering, applied mathematics, or a related
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of computational methods into clinically interpretable tools for bedside monitoring. Required Qualifications: PhD, MD, MD-PhD, or equivalent degree in biomedical engineering, electrical engineering, computer
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Qualifications: PhD in statistics, biostatistics, computer science, computational biology Required Application Materials: Please send a CV and include 2 references to [email protected](link sends e-mail
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biology and offer training in human histology, statistics, omics data analysis, computer vision, grant writing, and scientific publishing. Required Qualifications: 1. A doctoral degree (PhD, MD
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Qualifications: PhD in a relevant field is required; relevant fields include but are not limited to epidemiology, statistics, biostatistics, machine learning, data science, or other quantitative fields. Required
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for recent MD and PhD graduates who are passionate about leveraging computational methods to transform trauma and acute care surgery. Fellows will work at the intersection of clinical medicine, data
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mentoring access to have breadth of talented affiliated faculty members and consultants (e.g., Mirko Uljarevic, MD, PhD). Didactic and hands-on training in many theoretical and applied areas of research will
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, biomedical data science, genetics, and AI. (5) Lead and contribute to peer-reviewed manuscripts, conference presentations, and grant proposals. Required Qualifications: PhD, MD, MD/PhD, or equivalent doctoral