Advanced Process Controls Intern - Modeling & Optimization

Corning Incorporated; Painted Post (NY); On-site; USD 43,000 - 83,000; Full time

Job summary

Corning Incorporated is offering an Advanced Process Controls Intern role in the MT&E division in the United States. You will apply controls, optimization, data analytics, and machine learning to real manufacturing challenges, collaborating with experienced engineers on model-based control and predictive maintenance.

The internship provides hands-on experience with process data analysis, model development, and documentation, culminating in a final deliverable and presentation to stakeholders.

Qualifications

• Currently pursuing a degree in a technical field with coursework in process controls, optimization, data analytics, ML, or dynamic systems.
• Academic projects/internships in controls or data science are valued.

Responsibilities

• Support design, development, testing, and documentation of process controls solutions in manufacturing.
• Analyze process data, control performance, and trends to identify opportunities for stability, quality, throughput, or efficiency.
• Assist with modeling, system identification, simulation, and evaluation of PID and model-based control strategies.
• Contribute to model predictive control or other advanced-control concepts under mentorship.
• Build prototype optimization or analytics models using MATLAB, Simulink, Python, or related tools.
• Apply data analytics and ML techniques to process monitoring and predictive maintenance.

Skills

Process controls

Data analytics

Machine learning

Python

MATLAB/Simulink

Statistical analysis

Communication

Team collaboration

Education

Bachelor's/Master's/PhD in Engineering/CS/Math

Tools

Python

MATLAB/Simulink

Git

Data visualization

Job description

Corning Incorporated is offering an Advanced Process Controls Intern role in the MT&E division in the United States. You will apply controls, optimization, data analytics, and machine learning to real manufacturing challenges, collaborating with experienced engineers on model-based control and predictive maintenance.

The internship provides hands-on experience with process data analysis, model development, and documentation, culminating in a final deliverable and presentation to stakeholders.