Graduate Education

Our masters program is designed to educate individuals so that they have disciplinary knowledge and expertise in materials science and data science. Students are trained to have interdisciplinary perspectives and the necessary skills and tools to be able to understand and apply computational tools for modeling, simulation and informatics, together with experimental driven science so that they have the ability to contribute to and work to accelerate the pace of materials discovery and engineering design.

The Master’s degree in Materials Design and Innovation requires a minimum of 30 credit hours, and a minimum overall GPA of 3.0. The MS required courses are as follows:

Fall Compulsory Courses (3 credits each)

MDI 501  LEC Introduction to Materials Design and Informatics

MDI 502  LEC Quant Structure-Property Relationship in Materials

MDI 503  LEC Thermodynamics and Molecular Structure of Materials

MDI 504  LEC Multivariate Statistics and Materials Informatics 

Spring Compulsory Courses (3 credits each)

MDI 505  LEC Computational Materials Chemistry and Physics 

MDI 506  LEC Kinetics, Microstructure, and Defects 

MDI 507  LEC Quantitative Methods in Materials Characterization  

MDI 508  LEC Experimental Design for Materials Development

Summer/Fall (6 credits)

MDI 700 TUT  Semester Master’s Project 

• Students will have disciplinary knowledge in the areas of materials science and data science.
• Students will have the awareness and ability to query and work with databases in materials science.
• Students will acquire operational skills in statistics and data mining methods as applied to materials science.
• Students will have the ability to use computational methods in the analysis of experimental and/or simulation data.
• Students will develop relevant scientific literacy and have the ability to communicate in written and verbal formats.

The curriculum consists of the traditional and classical core foundations of materials science subjects but taught from the perspective of statistics, interpretation of databases and data mining methods. Beyond these core foundations, new distinctive courses in materials science that cover materials informatics, advanced computing methods and machine learning, robotics for materials engineering and an integrated “atoms to device” experimental development laboratory are offered. PhD students will also interface with UB’s Computational Data-enabled Science and Engineering graduate program, providing intensive training in all facets of computational data science that would be of value to both experimental and computational materials scientists.

The PhD degree in Materials Design and Innovation requires the following:

• Successful completion of the core course requirements, a minimum overall GPA of 3.0, and a project as per the MS degree
• Passing of a PhD comprehensive exam based on the core graduate courses in MDI
• Completion of 9 additional credits based three advanced level courses in MDI or related discipline
• Completion of PhD thesis

• Students will have in-depth knowledge in the areas of materials and data sciences, as well as well as the knowledge needed to integrate these fields.
• Students will have the critical thinking skills to define a research question and an appropriate strategy for developing a viable research proposal.
• Students will learn how to identify a materials science problem, either computational or experimental, and how an interdisciplinary approach that includes data analytics can find a solution to that problem.
• Students will develop familiarity with the interrelationship between experimental and computational perspectives of any given research problem in materials science.
• Students will have the ability to learn to clearly write and verbally present advanced scientific concepts.
• Students will have an understanding of the broad skills needed to advance their careers and some proficiencies in those skill-sets.