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Field
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significant mathematical and computational background to learn and develop new AI methods. While demonstrated experience in computer vision and deep learning for pathology or other biomedical image analysis is
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Associate will contribute to ongoing projects and have the opportunity to develop independent research aligned with the aims of the ADN lab. Current work focuses on machine learning and multivariate decoding
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responsibilities Design, implement and benchmark deep machine learning models for large-scale cancer datasets that include genomics, transcriptomics, epigenomics and imaging data Collaborate closely with
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difficult and the creation of more intelligent process control strategies and innovative methods of tracking reliability can be achieved with expert informed machine learning techniques, which offer more
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difficult and the creation of more intelligent process control strategies and innovative methods of tracking reliability can be achieved with expert informed machine learning techniques, which offer more
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national human rights courts, tribunals, mechanisms, and transitional justice processes, and propose potential pathways to justice for victims. This position relates to the second part of the project
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integrates OLA production of liposomes, trap arrays, local light/heating modules, and selection and sorting routines. Guided by machine learning, we will perform directed evolution experiments where we
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approaches (based on functional programming abstractions) to optimize the implementation of machine learning models and other digital signal processing algorithms on a specific FPGA architecture to fit within
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 6 hours ago
, designing natural language interfaces for more intuitive navigation of the BDC environment, creating BDC-specific foundation models, and enabling large language models (LLM) and machine learning-based
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biology, super-resolution microscopy, live-cell imaging, multi-omics, and mouse disease models to understand insulin-secretion deficiency and synapse degeneration. (See https://www.mcw.edu/departments/cell