AI/Math/Stats Students - Why Should I Join the aiM Program?

  1. First, this program is NOT designed to turn you into a materials scientist, rather help you be a better AI researcher, capable of excelling in interdisciplinary teams. Like statistics and applied math, AI doesn't exist in a vacuum but rather in the context of good problems - some of which can yield application for solutions to global challenges. You may not have heard of materials science, but it is currently undergoing a data and computational revolution, in which AI is helping to design better materials at an impressive, accelerated rate. Materials scientists (and other scientists in other fields) would love to have access to good AI algorithms, which is where you come in.
  2. Materials science problems can be very beautiful mathematically. They can be combinatorially hard, can involve building physics into AI, and there are a huge number of scientific problems that fall under the umbrella of materials science. Materials science doesn't limit you to one AI technique 0 it opens your eyes to many. Materials data is much easier to obtain than health care, criminal justice, or social media data and there is a big potential for cutting edge impacts - if you have the right collaborators and teaming skills - which is what this program is designed to give you.
  3. Every AI researcher knows that without a good problem, you can't create a good technique. This program is designed to inspire you - to learn about new fields, to see into a field that is up and coming (and really important) - so that you can design the best AI techniques possible. Anything you learn in materials science will probably be applicable to all of science...and beyond. If you want to be a top researcher in AI or use AI tools for scientific discovery, this is the program to choose.
  4. Our aiM program is not designed to limit you to a new and less known field. In fact, quite the opposite; this program is designed to give you the perspectives, skills, and teamwork experience you will need to become a successful AI researcher as well as broaden your network and career path options.