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Materials Science/Engineering/Chemistry/Physics students: Why should I join the aiM program?
- First, this program is NOT designed to turn you into a computer scientist, rather to help you leverage data science and machine learning to be at the forefront of materials discovery and innovation in an interdisciplinary team. Materials science began with experimentation and theory, has blossomed with increasingly detailed capabilities of modeling across length scales, and is now poised to utilize AI to solve unanswered questions about all types of material systems. This program prepares you to be a leader in this new era of materials discovery.
- That said, this program will expose you to computational and mathematical frameworks and concepts that are not encountered in a typical materials science curriculum. The variety of AI and ML approaches covered will expand your perspective on what data and uncertainty even mean, and has a high likelihood of covering a particular technique, algorithm, or software tool that will be individually game changing.
- This program is not only for students interested in simulation and modeling. AI opens many new possibilities for learning from experimental data sets. In fact, experimental data is rich in complexity and layered with many complicating factors and confounding conditions which often cannot be controlled. Experimental data is also often incomplete, leading to missing fields that should be interpolated intelligently. Finally, repositories of experimental data are rapidly growing, enabling access to significant quantities of experimental data not only from your own work but also from related experiments by others.
- Our aiM program arms you with fundamental understanding and skills in AI which will enable you to utilize ML codes on your own and to partner with collaborators who are experts in AI algorithm development and can work with you to hone a new algorithm to your material problem. This program is designed for you to acquire the perspectives, skills, and teamwork experience you will need to be the most successful researcher on materials problems as well as broaden your network and career path options.