Internship - Advanced Control & Optimization
Pubblicato il 05-10-2026 - BlackBerry in Genova
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 ManagerWe 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 responsibilitiesSupport the development and validation of dynamic plant models using Modelica language for power generation plants and steam networksSupport the identification of empirical process models using historical plant data for advanced control applicationsValidate models against real plant data and performance specificationsSupport advanced process control projects based on multivariable Model Predictive Control (MPC) using ABB Predict & Control technologyContribute to the identification of controlled variables, manipulated variables, disturbances, operating constraints, and optimization objectives for industrial process unitsAssist 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 mannerSupport the development of technical documentation regarding advanced control projectsCollaborate on optimization projects using ABB OPTIMAX technology. Develop optimization models for steam and power system