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Field
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algorithms for the scanner using machine learning and deep learning. Qualifications: The position requires some background in machine learning, optimization, and deep learning. Some familiarity with MR physics
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extended to 2 years. The primary focus of this research will be focused on optimization of multimodal treatment of pancreatic cancer (clinical outcome research). In this role, you will be expected to work
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
and professional sustainability. We optimize our partnership with the UNC Health System through close collaboration and commitment to service. OUR VISION Our vision is to be the nation’s leading public
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of species, including horses, cattle, pigs, rats, mice, sheep, and birds and to extend efforts at optimizing performance and health in humans and livestock. • Assist with writing grant proposals, manuscripts
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-performance computing. Additional experience in DNA biophysics, machine learning, and optimization is preferred. This job description intends to provide a representative and level of the types of duties and
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experiment, as well as in the commissioning, optimization, and development of analyses for the ALPHA experiment. The candidate is also expected to take a leadership role in JHU-based testing toward
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(toliaslab.org (link is external) ), Tirin Moore (moorelabstanford.com (link is external) ), and other collaborators at Stanford. Role & Responsibilities: Design and optimize large-scale electrophysiological and
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or Oropouche viruses). Other projects include improving risk assessment, optimizing surveillance system design, and developing and evaluating mitigation strategies. These projects aim to integrate epidemiology
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of deterministic and stochastic dynamical systems, optimal control, network models, and machine learning. Preference will be given to candidates with experience in these areas. The researcher will work closely with
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areas Biomedical applications, social determinants of health or other demographic health areas Spatial microsimulation, spatially weighted regression, combinatorial optimization or Bayesian network