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workers, staff, and faculty to teach and support these workshops. 3. Assist with the development and support of funded DH scholarship, both at USM and at partner institutions across the state, including
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for the EAP and Cornell community Participate in EAP and Center for International Studies initiatives that relate to the scholar’s work or interests No teaching required. However, if the scholar wishes to teach
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Investigator, the Postdoctoral Associate will conduct specialized cardiovascular research techniques and procedures with focus on artificial intelligence and machine learning platforms that will promote
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management machine learning, distributed computing, and resource optimization leveraging the unique computational resources available at ORNL, including the Frontier supercomputer—the world's first exascale
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Work Experience M.D. or PhD Required Qualifications A qualified candidate must hold a doctoral degree in biology or biomedical sciences. A combination of skills in cell culture, animal disease models
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and networking, with a particular focus on 5G and Beyond 5G technologies and applications of artificial intelligence and machine learning to wireless systems. The candidate will oversee the design and
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imbalances. A fundamental understanding of classical Machine Learning Techniques for longitudinal data analysis. An understanding of probability theory and basic frequentist statistical approaches
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bioinformatic approaches, including AI and machine learning, to analyze both existing and newly generated transcriptomic datasets. Benefits at UTA We are proud to offer a comprehensive benefits package to all our
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data collection and management Data analysis and model building Develop advanced deep learning and machine learning algorithms Assist with organizing large scale multimodal neuroimaging datasets, brain
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Bioinformatics and/or Cheminformatics. Experience working in computational drug discovery, particularly multiscale applications. Experience working in Python and Bash. Understanding of machine/deep learning topics