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Field
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, evolutionary biology, computer science, physics, applied mathematics, or engineering. Our research integrates mathematical modeling, machine learning, and quantitative experiments to understand and control
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develop novel computational approaches. Develop mathematical descriptions for the acquired data and work with our theorists collaborators to implement new theories. Integrate with the rest of the lab and
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master's degree (or equivalent) and PhD in Mathematics/Statistics/Data Science Research expertise in the analysis of complex systems Familiar with network analysis, concepts of resilience (e.g. adaptive
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mathematical background Skills: Seismic station installation and operation, computer coding, seismic data processing, strong written and oral communication, experience with manuscript development, experience
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Postdoctoral Associate AI and MRI Required Qualifications: (as evidenced by an attached resume) Doctoral Degree (or foreign equivalent) in Electrical and Computer Engineering, Computational Science
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). Applicants with a PhD in a quantitative field (computational biology, bioinformatics, systems biology, genetics/genomics, statistics, mathematics, computer science, or related fields) are encouraged to apply
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years ) Ph.D. in Engineering, Operations, Computer Science, Mathematics or a related field. Knowledge of optimization, power systems operations and planning, electricity markets, issues surrounding
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mathematics, bioengineering, chemistry, chemical engineering, or a related field of experience. Excellent verbal and written communications skills, as well as oral presentation skills. Organization and time
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visual representation and analysis of large-scale 2D/3D scientific data. This position resides in the Data Visualization Group in the Data and AI Systems Section, Computer Science and Mathematics Division
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Interdisciplinary Training in Mathematics for Human Health,” supported by the National Science Foundation. RTG themes include modeling in cancer biology, computational neuroscience, and mathematical epidemiology