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R&D Engineering - Disposables Co-Op at Gentuity

Sudbury, Massachusetts, United States -

Full Time

Start Date

Immediate

Expiry Date

09 Jul, 26

Salary

0.0

Posted On

10 Apr, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Mechanical design, Statistics, GD&T, Technical communication, Data analysis, Biomedical image analysis, Medical device design, Prototyping, Root cause investigation, Risk analysis, Product design, Manufacturability, Cost reduction, Cross-functional collaboration, Attention to detail

Industry

Medical Equipment Manufacturing

Description

Description Design and prototype concepts using real-world data and evaluation methods Conduct hands-on testing including simulated use, mechanical testing, and root cause investigation Implement product design changes with a focus on improved performance, manufacturability, and cost reduction Make data-driven design decisions using statistics and risk analysis techniques Complete change impact assessments of design updates with cross-functional input Assist in additional R&D activities as needed Other duties as assigned Requirements EXPERIENCE/SKILL REQUIREMENTS: A working knowledge in the following areas: Experience with mechanical design Working knowledge of basic statistics and GD&T Ability to analyze, understand, and communicate technical information Organization and attention to detail Adept at managing multiple tasks, prioritization and working with others Experience with analysis of biomedical image data a plus Interest in medical device design, engineering, or manufacturing EDUCATIONAL REQUIREMENTS: Rising junior or senior pursuing a Bachelor of Science in biomedical engineering, mechanical engineering, chemical engineering, physics, or a related technical area.

Responsibilities

The intern will design and prototype concepts using real-world data and conduct hands-on testing including mechanical evaluations and root cause investigations. They will also implement product design changes to improve performance and manufacturability while performing data-driven design decisions.