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Field
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. The research involves the development of machine learning algorithms and MR pulse sequences for next-generation computational MRI. The research will be conducted at the Electrical and Computer Engineering and
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stimulating environment with some of the world?s top researchers and physicians. The qualified candidate will specifically focus on developing new algorithms for the analysis of epigenomic datasets derived from
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: Artificial Intelligence, including but not limited to Machine Learning, Responsible AI, and Computer Vision; Theoretical Computer Science, including Algorithms, Algorithmic Fairness, Game Theory, and Learning
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comprehensive scheduling algorithms) and handle sensitive information with confidentiality. Ability to work independently on a wide variety of tasks – both simple and complex - with minimal supervision and
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networks, transformers, and diffusion models. Proven experience building AI solutions using classical ML algorithms such as decision trees, gradient boosting machines, and shallow neural networks
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supporting multiple probes simultaneously. Swarms also provide the usual benefits of multi-element array reception, namely robustness to single point failures and transmit/receive diversity. The downside
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algorithms from concept to implementation; and performing systems integration and testing for technology maturation. Minimum Qualifications: 1. Ph.D. in relevant technical field 2. 6 years experience in
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limitations or potential issues with datasets and data types that may impact performance from machine learning algorithms. Re-trains models as needed to address new challenges or novel goals. Aids investigators
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responsibilities – position supports the Cancer Biology Program, with the expectation it will interface with multiple research teams with varied research interests, projects and timelines Qualifications Requirements
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functional imaging to better understand disease pathophysiology, to discover new therapeutic targets, and to develop novel diagnostic algorithms that can improve patient care. Specific areas of research