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will develop novel statistical and machine learning methods for any of the following: multi-omics data (such as bulk and large-scale single-cell RNA sequencing data, spatial transcriptomics, bulk and
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limited to, patient-specific, monthly, daily, and annual QA, machine and equipment acceptance/commissioning, imaging technology, treatment or diagnostic planning, special procedures, and radiation safety
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limited to, patient-specific, monthly, daily, and annual QA, machine and equipment acceptance/commissioning, imaging technology, treatment or diagnostic planning, special procedures, and radiation safety
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, United States of America [map ] Subject Areas: Engineering / Design Engineering , Software Engineering Artificial Intelligence / Biostatistics and Data Science Machine Learning / Data Science Appl Deadline: (posted 2024
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, including development of new computational tools for processing large-scale biospecimen data Creation of novel machine learning frameworks for automated scientific analysis and discovery Design and
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engineering, and solution architect team members to ensure that machine learning models are developed and evaluated through robust processes and effectively integrated into clinical care. This position will
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: Durham, North Carolina 27710, United States of America [map ] Subject Areas: Informatics Clinical Research Medicine / Artificial Intelligence, Machine Learning and Autonomy Appl Deadline: none (posted
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utilize new machine learning methods for 3D behavior tracking and analysis. · Advise PhD students on related projects. Other Work Performed and Expectations · Document progress consistently and
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theory, multi-objective optimization and machine learning. The specific project aims to understand the multiscale interactions shaping human gut bacteria and human gut pathogens. The project will combine
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the Bartesaghi Lab at Duke University to work in the development of image analysis and machine learning methods applied to protein structure determination using single-particle cryo-electron tomography (ET