Computational Science Ph.D. Learning Outcomes

  1. Describe and formulate a problem statement that requires computational tools to solve
  2. Compare, critically evaluate and choose from existing computational approaches or models, or develop new computational approaches or models for solving problems in physical, biological or engineering systems
  3. Formulate solutions within the limitations of available computational resources and data to develop and validate computational models
  4. Synthesize and assimilate data for improving the accuracy of computational models and the performance of computational methods
  5. Assess the accuracy, robustness and efficiency of numerical approaches and algorithms
  6. Use existing software and computational tools to conduct research and advance knowledge in an area of inquiry, and develop new tools as necessary that can be used, modified and advanced by others
  7. Document and communicate (orally and in writing) computational research and results to varied audiences and users
  8. Acquire, follow, and implement best practices in generating, handling, and analyzing data; develop the ability to critically question the design of algorithms and their purposes; abide by and promote scientific integrity and accountability

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