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Number: 494420 Department: Student Services, Law Salary: 65,300 - 74,300 Description: Responsible for the operations of a large program or center at the university. Oversees staff, budgets, and projects. 1
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 20 hours ago
, designing tools for data interpretation and visualization, and/or training foundation models and large language models (LLMs) for diverse biomedical applications. Dr. Li has published over 70 peer-reviewed
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Department: Inst for Ecological Resilience Salary: Commensurate with Experience/Education Description: Responsible for the operations of a large program or center at the university. Oversees staff
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-sensor data fusion, implementation and optimization of computer vision tools for novel applications, and optimization for either real-time or large- scale offline processing. Improve and maintain the ANP
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employees both personally and professionally. Job Highlights: A team of more than 400 professionals, Health System Information Services (HSIS) works to keep UAB Medicine's IT systems and infrastructure
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. This position is in the team led by Dr James Hay, based at Old Road Campus in Headington. You will be responsible for conducting detailed analysis of a large immunological dataset, including data from ELISA, PNA
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generating, mobilising, and harvesting “big data” to create a dynamic and agnostic collection of information and deliver a new class of research that will enable a better understanding of the clinical
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generating, mobilising, and harvesting “big data” to create a dynamic and agnostic collection of information and deliver a new class of research that will enable a better understanding of the clinical
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a visionary leader to head our high-performing Transformation Office and drive large-scale change across our complex University. Reporting to the SVP Operations and COO, you will work directly with
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models; 2. Statistical methods, analysis, and inference for large-scale computational simulator applications; 3. Uncertainty representation, quantification and propagation; and 4. Scalable data science