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Field
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purposes to meet multiple information and strategic requirements for the various stakeholders of the university. The successful candidate will join a team of other data analysts and data scientists to engage
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storytelling skills to produce videos that resonate with diverse audiences across multiple platforms. He/She will need to work closely with different stakeholders across NBS to achieve the intended impact for
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the future of pediatric oncology, neurodegenerative disorders, and sickle cell disease. Job Responsibilities: Analyze biomedical data with minimal supervision by performing advanced analysis, algorithm
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minimizing error and maximizing efficiency, is computationally challenging—no known polynomial-time algorithm exists to solve it optimally in all cases. Because of this complexity, researchers typically rely
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will include contributing to our clinical NLP tools, algorithms and interfaces used by clinical specialists. The post holder will be expected to be able to contribute in the following areas: Extend our
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; https://github.com/CogStack/MedCAT ) projects alongside any deployment specific enhancements and specialisations. This work will include contributing to our clinical NLP tools, algorithms and interfaces
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(RSE) Group. In the RSE Group, we collectively provide computational research expertise to multiple divisions within the University. As a central team of software experts, we are focused on improving
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and implements dynamic models, including machine learning algorithms, to optimize student-centered outcomes. Creates clear and actionable visualizations and dashboards using tools such as Power BI
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to multiple divisions within the University. As a central team of software experts, we are focused on improving the quality, performance, and sustainability of Princeton’s computational research software. Our
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-resource settings. This project aims to achieve several objectives, including the development of a new AI-algorithm and a paired dataset for comparing how different imaging techniques influence