Intern, Advanced Process Controls - Summer
Listed on 2026-10-02
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Engineering
Process Engineer, Automation & Mechatronics Engineer, Electrical Engineering, Manufacturing Engineer
Date: Sep 21, 2026
Location: Painted Post, NY, US, 14870
Company: Corning
Requisition Number: 78170
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.
Corning's Manufacturing, Technology and Engineering division (MTE) is recognized as the leader in engineering excellence & innovative manufacturing technologies by providing diverse skills to Corning's existing & emerging businesses.
We anticipate & provide timely, valued, leading edge manufacturing technologies and engineering expertise. We partner with Corning's businesses and the Science & Technology division. Together we create and sustain Corning's manufacturing as a differential advantage.
Role PurposeCorning Incorporated is a world leader in specialty glass and ceramics, focusing on keystone components that enable high-technology systems for consumer electronics, mobile emissions control, telecommunications, and life sciences. Corning's Manufacturing Technology and Engineering (MT&E) division is recognized as the leader in engineering excellence and innovative manufacturing technologies.
MT&E is seeking an Advanced Process Controls Intern who is interested in applying controls, optimization, data analytics, and machine learning to real manufacturing challenges. The intern will contribute to project work in a hands-on engineering environment while learning how advanced controls technologies are developed, tested, and transferred into manufacturing. This internship offers exposure to a broad range of Corning processes and opportunities to work with experienced engineers on model-based control, numerical optimization, process monitoring, fault detection, defect classification, and predictive maintenance.
Key Responsibilities- Support the design, development, testing, and documentation of process controls solutions for manufacturing processes while working in multidisciplinary teams.
- Analyze process data, control performance, and manufacturing trends to identify opportunities for improved stability, quality, throughput, or efficiency.
- Assist with controls-oriented modeling, system identification, simulation, and evaluation of traditional PID and model-based control strategies.
- Contribute to model predictive control, internal model control, or other advanced-control concepts under the guidance of experienced engineers.
- Build prototype optimization or analytics models using tools such as MATLAB, Simulink, Python, or related packages.
- Apply data analytics, statistical methods, or machine learning techniques to process monitoring, fault detection, defect classification, predictive maintenance, or continuous improvement problems.
- Work with process subject matter experts to understand manufacturing requirements, translate project needs into technical tasks, and communicate findings clearly.
- Prepare technical summaries, presentations, code, models, and documentation to share results with engineering and manufacturing stakeholders.
- Complete an internship project with defined deliverables and present outcomes, recommendations, and next steps at the end of the assignment.
- Currently pursuing a B.S., M.S., or Ph.D. in Electrical Engineering, Mechanical Engineering, Chemical Engineering, Systems Engineering, Operations Research, Computer Science, Data Science, Applied Mathematics, or a related technical field. Coursework or project experience in process controls, optimization, data analytics, machine learning, or dynamic systems is preferred.
- Prior industry experience is not required. Relevant academic research, coursework, capstone projects, internships, co-ops, or hands-on technical projects are strongly valued.
- Foundational understanding of process controls, dynamic systems, statistics, optimization, or machine learning.
- Programming experience in Python, MATLAB/Simulink, or a…
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