
Intern, Reliability and Inspection - Summer 2027
Corning, NYInternship$1,635–3,185/wkSeen todaySeen in employer's feed today
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Requirements
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Job overview
The Summer 2027 intern will help develop and validate laboratory methods for detecting and characterizing defects in brittle materials and multi-material structures. Under technical staff guidance, the intern will set up sensing and inspection systems, run reliability experiments, analyze waveform and image data, and compare detections with independent ground truth. Projects may focus on acoustic or ultrasonic monitoring, automated imaging and machine vision, or both.
Skills & qualifications
Skills
Qualifications
Full job description
Requisition Number: 79617
**The company built on breakthroughs. **
**Join us. **
Corning is one of the world’s leading innovators in glass, ceramic, and materials science. From the depths of the ocean to the farthest reaches of space, our technologies push the boundaries of what’s possible.
How do we do this? With our people. They break through limitations and expectations – not once in a career, but every day. They help move our company, and the world, forward.
At Corning, there are endless possibilities for making an impact. You can help connect the unconnected, drive the future of automobiles, transform at-home entertainment, and ensure the delivery of lifesaving medicines. And so much more.
Come break through with us.
Scope of Position
The Summer 2027 intern will support the development and validation of laboratory methods that detect and characterize small defects in brittle materials and multi-material structures, either as damage forms during thermal-mechanical reliability stresses or through inspection afterwards. The work will establish what each method can and cannot detect, and how those detections relate to underlying failure mechanisms.
Under the guidance of technical staff, the intern will set up and calibrate sensing and inspection systems, run reliability experiments, analyze waveform and image data, and confirm detections against independent ground truth from microscopy, fractography, sectioning, materials and property characterization and failure analysis. Depending on interests and program needs, the project may focus on acoustic emission or ultrasonic monitoring during thermal cycling, on commissioning and applying an automated imaging and machine vision inspection system, or on a combination of both. Results will also help calibrate physics-based models and empirical reliability predictions.
Program Benefits
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Competitive salaries
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Housing assistance
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Travel reimbursement
Intern Activities
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Social and networking events
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Volunteer opportunities
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Community Involvement
Key Responsibilities
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Review literature on non-destructive evaluation, acoustic emission and ultrasonic sensing, optical inspection, and reliability mechanisms in brittle materials and electronic packaging.
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Plan and run experiments, including building and calibrating sensors, data acquisition systems, and test or inspection setups.
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Apply acoustic emission or other ultrasonic methods to detect, locate and time damage during thermal cycling and other reliability-related stressors.
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Commission and apply a laboratory imaging system, including automated image analysis and machine vision for defect detection.
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Acquire, process and analyze sensor waveforms and image data using MATLAB, Python or similar data-analysis tools.
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Correlate detected events with independent ground truth from microscopy, sectioning, materials characterization and failure analysis; quantify detection thresholds, noise and false calls, and identify which damage mechanisms can and cannot be detected.
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Use collected data to help calibrate physics-based modeling predictions and develop empirical reliability predictions and associated models.
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Document methods so others can repeat them, follow laboratory safety practices, and communicate findings clearly in written reports and presentations.
Requirements
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Currently pursuing a graduate degree (PhD preferred) in mechanical, materials, reliability, electrical or computer engineering, applied physics, optics, or a closely related field.
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Research, coursework, or hands-on laboratory experience in at least one of: acoustic emission, ultrasonics or non-destructive evaluation; optical imaging or machine vision; reliability testing, life modeling or failure analysis.
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Experience with signal or image processing using MATLAB, Python or similar tools.
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Ability to follow laboratory safety procedures, experimental protocols, and data-documentation practices.
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Strong analytical and problem-solving skills, with attention to detail and a willingness to learn new hands-on laboratory techniques.
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Ability to organize, analyze, and communicate experimental results clearly in written and verbal formats.
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Ability to work collaboratively with scientists and engineers while independently completing assigned tasks.
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Must be available for 10 weeks during Summer 2027 (May-August 2027) with a graduation date of December 2027 or later
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Be interested in working for Corning, Inc after graduation, if presented with a full-time job opportunity.
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Be willing to work at the posted job location
Desired Skills
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PhD research in non-destructive evaluation, acoustics/ultrasonics, or imaging, applied to reliability of electronics and semiconductor packaging.
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Experience with acoustic emission sensors, waveguides, source location, waveform feature extraction, or laser vibrometry.
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Experience setting up cameras, optics, motion stages or automated inspection systems, including machine-learning-based image analysis.
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Experience with reliability testing of electronics or semiconductor packages, such as thermal cycling or environmental stress testing.
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Knowledge of brittle materials, glass, fracture mechanics, or thermal-mechanical modeling.
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Experience with microscopy, cross-sectioning, sample preparation, or other materials characterization methods.
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Familiarity with experimental design, statistical data analysis, and technical literature review.
This position does not support immigration sponsorship.
The range for this position is $1,635.00 - $3,185.00 biweekly. Starting pay for the successful applicant is prescribed based on geographic location, nature of position, and year in school.
**A job that shapes a life. **
We prohibit discrimination on the basis of race, color, gender, age, religion, national origin, sexual orientation, gender identity or expression, disability, veteran status or any other legally protected status.
Corning is committed to providing equal employment opportunities and considers requests for reasonable accommodations in accordance with applicable laws. Individuals with disabilities or sincerely held religious beliefs may request reasonable accommodations to participate in the application or interview process, perform essential job functions, or access other benefits and privileges of employment. To submit a request for reasonable accommodation related to disability or religion, please contact us at [email protected] .
How this job compares
Set against the 558 open Reliability Engineering jobs on Olive Jobs, counted November 7, 2026.
- Pay
- This posting$1,635–3,185/wk
- US median$146–235K/yr435 salary ranges
- US median$31–40/hr30 hourly ranges
- Openings
- Olive Jobs lists 23 open Reliability Engineering jobs in New York and 558 across the US. 2% of them nationwide are listed as remote or flexible.
- Hiring the most in New York
- Global Foundries10 open
- Oracle3 open
- Corning Incorporated (this employer)2 open
- Experience
- Reliability Engineering postings that state a minimum ask for 7 years of experience at the median; the middle half ask for 5 to 10 years (463 postings).
- Education
- This posting asks for a master's degree; 4 of the 558 open Reliability Engineering jobs (under 1%) ask for a master's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 7, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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