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PhD in Machine Learning, Medical Images, and Disesae Prevention
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Predoctoral fellowship in Translational Cardiovascular Disease Research in 2021-2022 academic year at the Geisinger Health System and the University of Massachusetts Lowell Qualifications: • a Bachelor's or equivalent degree in engineering (Mechanical, Electrical, or Computer), Computer Science, Applied Mathematics, or related fields. Applicants with a master's degree are preferred. • Previous research experience is highly desirable. Desirable research skills include medical image processing, machine learning, and programming (C, C++, or Python). • Strong oral and written communication skills. The research tracks will include the following: 1) Cardiovascular imaging, including fetal, pediatric, and adult congenital heart disease methodologies and translational research. Examples include Fetal circulation and coarctation in fetus using fetal echocardiography, cardiac MRI, computational fluid dynamics, and machine learning. 2) Cardiovascular disease genomics, risk stratification and prevention in childhood. Examples include computer interpretable guidelines, clinical decision supporting system, machine learning, and deep learning applied in cardiovascular genomics, risk stratification and prevention in children. Interested students should send a single PDF containing the following items to “sge@geisinger.edu” and “ZhenglunAlan_Wei@uml.edu” with a " PhD candidate in Translational Cardiovascular Disease Research in 2021-2022" in the subject line. • Curriculum Vitae • Unofficial Transcripts • Contact information for three references |
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