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Field
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. Qualifications for this position include a PhD in Computer Science, Artificial Intelligence, Natural Language Processing, Human-Computer Interaction, or a closely related field. Candidates should have demonstrated
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: PhD in a scientific field Preferred experience: Strong programming and neuroimaging analysis experience. Familiarity with longitudinal modeling or machine learning techniques is desirable. Why MCW
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, Computing and Computational Sciences Directorate, at Oak Ridge National Laboratory (ORNL). This position presents a unique opportunity to develop cutting-edge high-performance computing (HPC) and machine
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at the intersection of AI/deep learning, bioinformatics, mathematical modeling, computational topology, scientific machine learning, for systems biology, single-cell genomics and protein design. The candidates will
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Biomedical Science related Master´s degree or DVM degree in addition to a PhD are preferred. This position will require attention to detail, leadership abilities, problem-solving skills, and a passion for
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degree or DVM degree in addition to a PhD are preferred. This position will require attention to detail, leadership abilities, problem-solving skills, and a passion for hands-on work, and caring
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sciences, computer science, machine learning, and education research. Research Themes The research themes identified for the NTO postdoc include, but are not limited to, the following: Developing
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. Minimum Education and Experience Ph.D in a related field. Preferred Education and Experience Preferred Education and Experience PhD in biomedical engineering, pharmacology, neuroscience, physiology
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. Demonstrated expertise in interdisciplinary research with technical and clinical teams and patients desired. Experience leveraging machine learning for human musculoskeletal biomechanics applications desired
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. Contribute to the development of research grants for funding of lab training and research. MINIMUM QUALIFICATIONS PhD in neuroscience, neurobiology, machine learning, biomedical engineering, or related field