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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
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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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, evaluation and re-evaluation of patient status Ability to use computer and learn new software programs Able to document and communicate pertinent information using computer and/or paper documentation tools
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Location: Durham, North Carolina 27708, United States of America [map ] Subject Area: Electrical and Computer Engineering / Artificial Intelligence and Machine Learning (AI/ML) Appl Deadline: 2025/05/01 11
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at high risk of sepsis for treatment with antibiotics and intravenous fluids. During the internship, students will learn about the role of predictive analytics and machine learning in health care and will
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the execution and publication of investigations on medical imaging, modeling, and simulations. Prior research experience in CT imaging is preferred. Programming skills (C, Python, MATLAB, etc.) for machine
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of patient status Ability to use computer and learn new software programs and technology Able to document and communicate pertinent information using computer and/or paper documentation tools Knowledge in
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or computer and appropriately manage data transfer when required (5%) Contribute to the ongoing collection of administrative records and the writing of project technical reports, as needed (8%). Write and
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-evaluation of patient status. Ability to use computer and learn new software programs. Ability to navigate the entity to provide clinical care for patients. Ability to withstand prolonged standing and walking
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meetings and submission of assignments. Instructional support includes helping students learn how to prepare and file documents. Administrative functions (10%) will include organizing and calendaring