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Fellowship represents a unique opportunity to advance surgical care through innovative applications of data science and artificial intelligence. This interdisciplinary fellowship is designed for recent MD and
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brain-behavior relationships and inform evidence-based interventions for pediatric neurodevelopmental disorders. Key Responsibilities: Research Activities Design and implement neuropsychological and
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developments in sensor design, dataset transmission, data analysis, and numerical modeling to distinguish between normal and abnormal features. Here, the goal is to develop machine learning algorithms
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. Responsibilities may include: Designing and conducting studies on the clinical impact of GLP-1 and other metabolic therapies Developing and applying computer vision and machine learning techniques to analyze
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have the capacity to conceptualize, motivate, design, and implement original research on consequential, policy-relevant topics, and be able to take a leadership role in the research process. The Fellow
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confocal microscopy. · Ability to design, execute, and interpret independent experiments. · Excellent written and oral communication skills in English, with a strong publication record commensurate with
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these with functional genomics and molecular biology techniques to study their impact on physiology, we aim to better understand GPCR signaling and to provide a foundation for the design and testing of novel
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backgrounds trained in chemistry, chemical biology, microbiology, and/or biophysics fields. We have launched a collaborative antibacterial drug design program integrating chemical biology and mechanistic
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functions of extracellular vesicles (EVs) in modulating immune responses. Key Responsibilities: Design and execute experiments using a variety of techniques, including flow cytometry, CyTOF, spatial
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, CRISPR/Cas9 gene editing, immunofluorescence, flow cytometry, and confocal microscopy. · Ability to design, execute, and interpret independent experiments. · Excellent written and oral communication skills