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Field
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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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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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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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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 2 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
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Knowledge, Skills, and Abilities - Prior experience in somatosensory research. - Familiarity with advanced imaging, electrophysiological techniques, and behavioral assay methodologies. - Proficiency in using
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data analysis/spectral image processing. Use of data analytics or machine learning to guide process design and optimization. Job Family Postdoctoral Job Profile Postdoctoral Appointee Worker Type Long