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to candidates with strong training in metabolism or adipose biology, neuroscience, genomics, physiology, molecular biology, computational biology, or a related field, who are eager to build an interdisciplinary
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-disciplinary approach spanning human genetics, computational biology, genomics, genetics, pharmacology, and biochemistry. By integrating human population-scale data with experimentally tractable model systems
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motivated and skilled postdoctoral researcher to lead projects related to PhacoTrainer—computer vision models for cataract surgical video recognition. Project themes will include validating PhacoTrainer
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, FACS/flow-cytometry analysis, genetic manipulation of cells (e.g., CRISPR), and microscopy. Candidates with experience in computational analysis are encouraged to apply. The position is available
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are seeking motivated individuals wanting to make a difference in understanding brain autoimmunity and seeking to publish high impact publications in this growing field of interest. We work on the immunology
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. Xiaojie Qiu (Genetics & Computer Science)(link is external) and Dr. Matteo Molè (Obstetrics & Gynecology)(link is external) . Our goal is to explore the “black box” of early human pregnancy by mapping
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Health Epidemiology and Population Health Health Policy Med: PCOR Neuroscience Institute Medicine, Biomedical Informatics Research (BMIR) Biomedical Data Science Medicine, Center for Digital Health Postdoc
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distribution. Both projects will develop the Fontan emulator to be patient-specific, MRI compatible, computer controlled, and quantitatively evaluated using advanced bench-top, CFD/FSI simulation, and MRI-based
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precursors of breast neoplasia progress to invasive breast cancer. They will be part of an interdisciplinary team of pathologists, immunologists, and computer scientists. The project builds on our previous
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Departments and Centers: Pediatrics, Neonatal and Developmental Medicine Postdoc Appointment Term: 2 years, contingent upon excellent performance. Appointment Start Date: July 10, 2026 Group or Departmental