| Affiliations: |
Qian’s Materials Theory, Design, and Discovery Group
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| Project Leader: | Nathan Wilson wilsonnater@tamu.edu Materials Science & Engineering |
| Faculty Mentor: | Dr. Xiaofeng Qian, Ph.D. |
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Meeting Times:
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TBD |
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Team Size:
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4 (Team Full) |
| Open Spots: | 0 |
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Special Opportunities:
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Opportunities to present at conferences, co-author in papers, and continued research in our group
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Team Needs:
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Programing experience is required. Machine learning or data science knowledge is not required, but preferred. Basic chemistry and physics understanding is also preferred
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Description:
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Throughout history, the advancement of human civilization has largely been driven by new materials. Therefore, Significant effort has been put into designing and discovering new materials. Yet, much of the materials space is still left unexplored due to exponentially large number of possible materials. Modern computational models are often used to find new materials, however their computational costs to explore the material space is still too large. The goal of this project is to create a machine learning algorithm to explore the space while using the computational models to validate and train the machine learning algorithm, which will could bring down the computational cost significantly.
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