Training Overview

Pictures of students and instructor in classroomEach aiM-NRT PhD Fellow will engage in coursework integrated with parallel professional skills development and an experiential internship with opportunities to apply aiM training.

  • Boot Camp: A week-long orientation will provide fundamental knowledge in AI/DS+ Materials Science and development of professional skills (communication, collaboration, and teamwork skills).
  • Core courses:
      1. Fundamentals of Data Science for Materials Scientists  and/or
      2. Fundamentals of Materials Science for Data Scientists
      3. Applications in Data and Materials Science (SPRING ME 555/CS 590)
      4. Joint AI in Materials Capstone Project Course (year-long)
  • Experiential Internships: After two years of training in fundamentals and skills application, aiM Fellows will be prepared for an Summer (or extented) external internship with an industry partner or national laboratory. These collaborative internships will afford access to world-class expertise, unique experiments, and facilities to complement the skills aiM students learn through coursework and research to apply their skills to real-world problems in data-driven materials science and build their professional networks.
  • An ongoing professional development program: Thoughout the program experience students will develop professionally guided by an Individual Development Plan (IDP) including “professional skills” and “technical skills”. Professional skills training will include formal and informal communication as well as K-12 outreach, mentor and mentee training, leadership and collaboration skills, and other skills critical for workforce success.
  • Annual aiM-NRT Challenge Competition: Student teams from across the U.S. will submit projects that apply AI and machine learning to materials design.


aiM certificate



Training Schedule for aiM Certificate

Orientation Year 1 Year 2

Years 3-5

 Boot Camp

  • Overview
  • Materials+Data Science, and Statistics Fundamentals
  • Team Building
  • Professional Skills Development

Core Courses

  • Fundamentals of Data Science for Material Scientists and/or 
  • Fundamentals of Materials Science for Data Scientists
  • Applications in Data and Materials Science

Year-Long Core Course 

  • Joint AI in Materials Capstone Project Course

Experiential Training

  • Industry or National Lab Internship
  • Teaching or Mentoring Experiences

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