ENERGIZE Trainee Program

As an ENERGIZE Trainee you will have the opportunity to participate in research and professional development including workshops, seminars, and symposia. Additionally as a trainee you are required to take the Core NRT Course and two elective courses (one in data science and one in materials science).

The Core NRT Course introduces students to experimental, computational, and data science methods in materials science and how these methods can be integrated in research.

Courses across BU may be counted for your elective courses. Possible courses include:

Data science courses:

  • CASCS 523: Deep learning (cross-list with ECE- separate sections)
  • CASCS 531: Advanced optimization algorithms
  • CASCS 541: Applied machine learning
  • CASCS 542: Principles of machine learning
  • CASMA 679: Applied Statistical Machine Learning
  • CASMA 752: Mathematical Foundations of Machine Learning
  • ENGEC 503: Intro to learning from data
  • ENGEC 534: Discrete stochastic models
  • ENGEC 732: Combinatorial optimization and graph algorithms
  • ENGEC 710: Dynamic programming and reinforcement learning
  • CASCS 565: Algorithmic data mining
  • CASPY 580: Machine learning for physicists

Materials science courses:

  • CASPY 543: Intro to solid state physics
  • CASCH 550: Materials chemistry
  • CASCH 655: Statistical Mechanics
  • CASCH 652: Molecular Quantum Mechanics II: Dynamics and Spectroscopy
  • CASCH 743: Organometallic Chemistry
  • CASCH 658: Chemical Kinetics and Dynamics
  • CASPY 742: Solid-state Physics 1
  • CASPY 782: Advanced Materials Characterization
  • CASCS 630: Graduate Algorithms
  • ENGMS 503: Kinetic processes in materials
  • ENGMS 545: Electrochemistry of fuel cells and batteries
  • ENGMS 782: Advanced materials characterization
  • ENGME 714: Advanced stochastic modeling and simulation
  • ENGEC 771: Physics of compound semiconductor devices
  • ENGME 702: Computational fluid dynamics
  • ENGBE/MS 504: Polymers and Soft Materials
  • ENGEC 565: Introduction to Electromagnetics and Photonics
  • ENGEC 577: Electronic, optical, and magnetic properties of materials
  • ENGMS 539: Introduction to materials science and engineering
  • ENGMS 781: Electroceramics
  • CASCH 552: Electrochemistry
  • CASPY 745: Experimental surface physics and chemistry

Please note the list of elective courses is based on offerings across the university this semester and may not be exhaustive. Reach out to energize@bu.edu if you would like to know if a course will count towards the data science or materials science elective.