Scientific Computing
Team Goals
Computational modeling and simulation have become prime discovery tools in the era of data-driven science and engineering. Mathematical models and computer simulations are used in virtually every scientific discipline – including climate modeling, materials research, biophysics, and health informatics. The complexity of these problems requires efficient algorithms that integrate multiscale models and multimodal data. This VIP team focuses on how Scientific Computing leverages algorithms and data to explain complex phenomena and discover novel solutions in science and engineering. The topics will be aligned with ongoing research projects in Computational Science and Materials Informatics (CoSMIc Lab)
Research Topics
- Multiscale Models and Algorithms for Complex Systems
- Machine Learning and Artificial Intelligence for Discovery and Design
- Scientific Software Development
- Workflows for Reproducible Data Analysis
Majors That Fit
Any major where scientific computing is relevant, including but not limited to
- Computer Science
- Data Science
- Mathematics
- Physics
- Materials Science
Skills in one or more of the following areas will be beneficial (not all are required – you can acquire more skills during the VIP!)
- Engineering Mathematics (Calculus, Linear Algebra, Statistics)
- Programming (Unix Shell, C/C++, FORTRAN, Python)
- Data Science (Scikit Learn, TensorFlow, PyTorch)
- AI/ML (Regression, Classification, Neural Networks)
Contact
