Internship - Advanced Control & Optimization

At ABB , we help industries run leaner and cleaner—and every person here makes that happen. You’ll be empowered to lead, supported to grow, and proud of the impact we create together. Join us and help run what runs the world. This position reports to: Digital Solution Engineering Manager __ We are seeking a motivated recent graduate or final-year student in engineering to join our team as Plant Advanced Control and Optimization Intern.

This position offers a unique opportunity to work on cutting-edge advanced control and optimization projects for industrial plants, focusing on Power Generation and Energy Industries, using ABB's advanced multivariable model predictive control (Predict & Control) and optimization tool (OPTIMAX). The intern will also gain hands-on experience in plant modeling, using Modelica, process simulation and control system integration, working alongside experienced engineers on real-world industrial projects.

Your role

and responsibilities Support the development and validation of dynamic plant models using Modelica language for power generation plants and steam networks Support the identification of empirical process models using historical plant data for advanced control applications Validate models against real plant data and performance specifications Support advanced process control projects based on multivariable Model Predictive Control (MPC) using ABB Predict & Control technology Contribute to the identification of controlled variables, manipulated variables, disturbances, operating constraints, and optimization objectives for industrial process units Assist in developing, configuring, testing, and validating MPC applications to reduce process variability, improve energy efficiency, and operate closer to plant constraints in a safe and stable manner Support the development of technical documentation regarding advanced control projects Collaborate on optimization projects using ABB OPTIMAX technology.

Develop optimization models for steam and power systems Analyze plant performance data to identify optimization opportunities The work model for the role is: hybrid This role is contributing to the Process Automation Energy Industries in Central-South Europe region.

Qualifications

Master's degree (completed or final year) in Energy Engineering, Chemical Engineering, Mechanical Engineering and Process and Industrial Engineering. Technical Skills: knowledge of process simulation tools (MATLAB/Simulink, or similar) is a plus. Knowledge of process simulation tools (MATLAB/Simulink, or similar) is a plus.

Knowledge of OPC protocol and fieldbus communications is a plus. Knowledge of Windows O.S. and Linux. Interest in configuring and testing computer systems and network architecture. Basic programming skills (Python, MATLAB, or similar) is a plus. Proficiency in the Microsoft Office Suite, particularly Excel. Languages: Ability to communicate fluently in both Italian and English .

Soft Skills: A proactive mindset with strong interpersonal and communication skills.

Benefits

Flexibility and work-life balance: Flexible working hours, hybrid work options, and a strong focus on work-life integration. More about us ABB’s Automation business area enables customers to operate some of the world’s largest and most complex industrial infrastructures, helping them outrun – leaner and cleaner. We offer a broad range of automation, electrification and digital solutions for process, hybrid and maritime industries, including industry-specific integrated control and software as well as measurement and analytics solutions and services.

Join us. Be part of the team where progress happens, industries transform, and your work shapes the world. Run What Runs the World. Building a cleaner, smarter future takes all kinds of minds: the curious, the courageous, and the creative. That's why we welcome people from all backgrounds and experiences. Ready to make an impact?

Apply today or visit https://www.abb.com to learn more about the impact of our solutions across the globe.