Sr. TOD Controls Engineer

Date: May 25, 2023

Location: Wuhan, HB, CN, 430040

Company: Corning

Requisition Number: 60271


Corning is vital to progress – in the industries we help shape and in the world we share.

We invent life-changing technologies using materials science. Our scientific and manufacturing expertise, boundless curiosity, and commitment to purposeful invention place us at the center of the way the world interacts, works, learns, and lives.

Our sustained investment in research, development, and invention means we’re always ready to solve the toughest challenges alongside our customers. 

Corning’s Display Technologies segment manufactures glass substrates for active matrix liquid crystal displays (“LCDs”) that are used primarily in LCD televisions, notebook computers and flat panel desktop monitors.

Day to Day Responsibilities


  • Develop physics-based models of nonlinear, multivariable systems and subsequently embed the physics of those models into algorithms to control the system dynamics by utilizing advanced model-based control design techniques
  • Utilize machine learning methods to develop process monitoring and fault detection tools and/or classification/regression models for solving important manufacturing problems, such as defect classification, predictive maintenance, etc.
  • Build/develop supervisory control layer for calculating optimal setpoints for process control in a manufacturing system; this will require coordinating and synchronizing the existing physics-based/first-principles models to provide an overall plant process view.
  • Develop in-depth knowledge of Corning processes to build technical understanding for key process steps by using rigorous scientific knowledge on flow, mass/heat transfer, magnetic and electric fields
  • Lead project teams and work closely with process engineers to implement/deliver advanced control solutions and potentially other advanced process technologies
  • Work in a multi-disciplinary environment where there will be collaboration between process experts, data scientists, controls engineers, and modelers
  • Generate intellectual property through technical reports, invention disclosures, and patent applications


Education & Experiences

  • Ph.D. or Masters (+3 years of manufacturing experience) in Chemical, Mechanical or Electrical Engineering discipline
  • Direct experience with data analysis, machine learning (ML), advanced controls technologies and/or first-principles/physics-based modeling


Required Skills

  • Evaluate existing process control strategies and propose and develop enhancements. Utilize multivariate statistical methods and machine learning for process monitoring, fault diagnosis and isolation, defect classification, and/or predictive maintenance
  • Design and develop process controls solutions (especially model-based control techniques) for manufacturing processes. Work closely with manufacturing to develop appropriate hardware and software platforms for implementing control solutions.
  • Familiarity with optimization theory and controls technologies such as optimal control, robust control, adaptive control, model predictive control (MPC), non-linear approaches, and traditional PID control
  • Experience with developing data-driven (system identification) / physics-based models (finite element models, mass and energy balances, etc.) for manufacturing process optimization
  • Extensive knowledge of ML techniques/algorithms (e.g., neural networks, random forests, etc.) and their mathematical foundation
  • Proficient in Matlab/Simulink and working knowledge of Python, C/C++, .NET.
  • Must have: (1) a thorough understanding of relevant scientific concepts, principles, and theory, particularly relating to general machine learning and algorithms and fundamental physics principles; (2) experience demonstrating broad application of those concepts in real-world settings.


Desired Skills

  • Skills that can be demonstrated in PLC and IEC based programming (ladder, structured text)
  • Background in multivariate statistics tools, such as principal component analysis (PCA) and partial least squares (PLS) regression
  • Experience with real-time control systems, data acquisition, and data interpretation
  • Experience using machine learning packages such as Tensorflow/Keras, PyTorch, Scikit-Learn.
  • Experience with formal language models (finite state automaton (FSA), Petri net, Symbolic model, etc.), graph theory and finite abstraction
  • Ability to work in a manufacturing environment


Soft skills

  • Project leadership
  • Communication skills in a variety of situations – from gathering operator insight to stakeholder presentations
  • Collaboration across a multi-disciplinary group
  • Strong verbal and written skills
  • Excellent interpersonal skills
  • Ability to prepare and present presentations effectively
  • Functions well on projects and team initiatives as well as independent assignments
  • Strong technical curiosity with desire to take on challenging technical problems