Research Assistant in Materials Science and Additive Manufacturing
Position Information
The selected candidate will work on a funded research project focused on developing novel alloys for energy applications in harsh environments using additive manufacturing. This research involves integrating computational modeling, machine learning, and experimental investigations to design and characterize new alloys and composites fabricated via laser powder bed fusion additive manufacturing. This work is closely woven into materials science, additive manufacturing, and machine learning realm, with applications in energy and extreme environments.
Scope of Job
The maximum appointment is limited to twenty (20) hours per week (50% FTE) during the Fall and Spring semesters. The maximum appointment may be increased up to forty (40) hours per week (100% FTE) during the summer if funded by a grant.
Discipline Specific Required Qualifications
- Research Assistant assistantship award is available to master's and doctoral students who are assigned to a specific faculty member who is conducting research or a scholarly endeavor.
- Duties will vary depending on the project and assigned research/scholarly functions, or other creative aspects.
Preferred Qualifications
- Bachelor's degree in Mechanical Engineering, Manufacturing Engineering, or Materials Science and Engineering.
- Master's degree in Mechanical Engineering or Materials Science and Engineering (required for Ph.D. applicants).
- Experience with additive manufacturing, materials characterization, and/or physics-informed machine learning.
- Proficiency in Python programming is preferred.
Salary
Commensurate with experience.
Benefits
The selected candidate will receive a monthly stipend and tuition support.
Qualifications
The Research Assistant assistantship award is available to master's and doctoral students who are assigned to a specific faculty member who is conducting research or a scholarly endeavor. Duties will vary depending on the project and assigned research/scholarly functions, or other creative aspects.
Skills
Experience with additive manufacturing, materials characterization, and/or physics-informed machine learning. Proficiency in Python programming is preferred.
Pay
Commensurate with experience.
Schedule
The maximum appointment is limited to twenty (20) hours per week (50% FTE) during the Fall and Spring semesters. The maximum appointment may be increased up to forty (40) hours per week (100% FTE) during the summer if funded by a grant.
Benefits
The selected candidate will receive a monthly stipend and tuition support.