Research Assistant, ML for Materials (Hybrid)

University of Michigan-Flint School of Management; Flint (MI); Hybrid; USD 20,000 - 29,000; Part time

Job summary

The University of Michigan-Flint invites applications for a part-time Research Assistant I (TEMP) on the Flint Campus. You will work with Dr.

Bin Wang on developing machine learning algorithms for studying material structures, properties, and applications, with possible experimental work. Under the professor's guidance, you will curate datasets, build graph neural networks to predict properties such as ionic conductivity and stability, and present findings in team meetings and research fairs

Qualifications

• Must be a UM-Flint Undergraduate student.
• Have taken or are currently enrolled in CHM 260 (General Chemistry I).
• Willingness to learn, or have taken/are currently enrolled in, an introductory programming or data science course.

Responsibilities

• Curate and analyze datasets of superionic conductors' structures and properties.
• Build and train machine learning models (especially graph neural networks) to predict materials properties (e.g. ionic conductivity, stability).
• Communicate and present findings in team meetings, research fairs conferences (with support from the professor).

Skills

Coding skills

Chemistry and materials skills

Job description

The University of Michigan-Flint invites applications for a part-time Research Assistant I (TEMP) on the Flint Campus. You will work with Dr.

Bin Wang on developing machine learning algorithms for studying material structures, properties, and applications, with possible experimental work. Under the professor's guidance, you will curate datasets, build graph neural networks to predict properties such as ionic conductivity and stability, and present findings in team meetings and research fairs