Position Overview:
The Development Process Engineer/Technologist designs and executes experiments to advance novel metal additive manufacturing processes. Collaborating with senior engineers and technologists, this role contributes to the development of project plans, creates detailed experimental designs, analyzes results, and supports the transition of new processes from concept to implementation.
Job Responsibilities
Define experiments based on detailed understanding of physical mechanisms and hypotheses; parametrize cause and effects of experiment; analyze experimental data using statistical tools; clearly organize and track parts and data.
Work independently to execute experiments from preparing solid models, convert to files that can be printed, schedule files to be printed, troubleshoot issues that occur during printing and analyzing parts after print.
Perform all post-build analysis including metrology measurements such as tensile properties, surface roughness measurements, metallographic analysis, and printer sensor data.
Make detailed observations of experiments and note any anomalies on the tool during the run and troubleshoot any anomalies.
Interface with software/hardware engineers to troubleshoot and implement required changes to enable production of novel metal 3D parts.
Analyze in-build metrology data to gain insight into mechanisms of variable part performance.
Responsible for recording all data in a summary presentation for each experiment and presenting results to broader audience.
Maintain individual and team professional development by reading complex scientific papers and
highlight key phenomena and learning.
Follow procedures to operate 3D Printers in lab.
Participate in team and other assigned meetings.
Other duties as needed or required.
Requirements
Post-graduate degree in Materials Science, Chemical Engineering, Physics or related field is preferred; or Bachelor’s degree with 3 years of applicable experience
Competence in analyzing and interpreting data using common data analysis software such as Python, Matlab, or similar.
Strong knowledge of DOEs and statistics
High commitment to contribute to a positive, high paced and results oriented work environment
Experience defining and conducting experiments based on required learning; parameterizing cause and effects of experiment, and analyzing experiments data using statistical tools included in software such as JMP or similar
Ability to organize parts and data
Committed to quality, safety and communication
High level of accountability
Skilled in communicating, both verbal and written, on experimental and other results; and reading complex scientific papers and highlight key phenomena and learning
Attention to detail
Team-oriented and self-directed
Ability to quickly absorb and efficiently incorporate changing project needs
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