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University of Massachusetts Medical School | Shrewsbury, Massachusetts | United States | 16 days ago
more complex case reviews as needed, in addition to performing activities related to data mining, data analysis and recoveries. With increasing independence, the Investigator II is assigned to multiple
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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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network performance across multiple layers and levels of abstraction The ideal candidate will possess strong expertise in quantum communication and networking, with a solid command of both theoretical
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brain--a "digital twin" that captures neural activity and intelligent behavior at unprecedented scale and resolution. This ambitious project spans multiple institutes including the Wu Tsai Neurosciences
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. This position requires developing bioinformatics pipelines, applying variant interpretation algorithms, project management skills and communicating with diverse stakeholders to gather and articulate requirements
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within the MPOG registry. MPOG utilizes clinical phenotypes to identify cases for inclusion in research or quality improvement initiatives. Phenotypes are coded building blocks or algorithms used to sort
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of the AI algorithms. Key duties Develop a robust framework to simulate streamflow decomposed into fast-flow and baseflow at multiple Moroccan watersheds. The candidate would have to test various fast-flow
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of recommendation algorithms based on multiple data related to microorganisms and pathogens, and the implementation of the recommendation system on a testable platform. The work also includes the writing of technical
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transport problems across the fission and fusion energy fields. These areas include application of cutting-edge high performance computing algorithms, workflows, and methods to solve problems related
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healthcare application needs to analyze sensitive patient data across distributed nodes. Researchers and students can explore privacy-preserving algorithms and technologies like federated learning and zero