Research Assistant - College Of Enigneering - Department Of Mechanical Engineering

Carnegie Mellon University

Pittsburgh, PA, US
Pyy basis: hourly; base: not specified; benefits: ...
Experience with eos m290 pbf-lb/m machine
Data analysis using python programming
4+ years research in metal additive manufacturing
The role involves collecting experimental data to determine the link between spatter particles and porosity in laser powder bed fusion of metals

Job Summary

  • The role involves collecting experimental data to determine the link between spatter particles and porosity in laser powder bed fusion of metals.
  • Candidates will analyze data using Python and train machine learning models while collaborating with a multidisciplinary team of professors and researchers.
  • Carnegie Mellon University offers comprehensive benefits including medical insurance, retirement savings, tuition benefits, and free transit passes.

Matching Summary

The role involves collecting experimental data to determine the link between spatter particles and porosity in laser powder bed fusion of metals.

Salary

Pay Basis: Hourly; Base: Not specified; Benefits: Comprehensive medical, dental, vision, retirement, tuition, paid time off

Skills & Requirements

Must-have

  • Experience with EOS M290 PBF-LB/M machine
  • Data analysis using Python programming
  • 4+ years research in metal additive manufacturing
  • Process monitoring sensors infrared cameras
  • High-speed camera usage for spatter analysis

Nice-to-have

  • Multidisciplinary team collaboration skills
  • Academic manuscript writing experience
  • Machine learning model training and validation
  • Weekly presentation communication abilities

Key Requirements

  • Preferred doctorate degree in Mechanical Engineering or related field
  • 3-5 years of relevant professional experience
  • Successful background check required
  • Demonstrated expertise in metal additive manufacturing space

Work Rights

Not specified

Tailored Resume

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