Graduate Engineering Intern – Model Based Controls

Daikin Applied Americas•Plymouth, MN

1d•Hybrid

About The Position

Join the world's largest HVAC company, named by Forbes as one of America's Best-In-State Employers 2025! Graduate Engineering Intern –Model Based Controls – Plymouth, MN – Hybrid Make your mark at the world’s largest HVAC company Daikin Applied is seeking a highly motivated graduate engineering student for a full-time, 10 month engagement as a Graduate Engineering Intern (Model Based Controls). The Model-Based Controls Engineering Intern will play a critical role in advancing the tools, methods, and best practices that enable model-based controls development across the Applied Air Handlers, Chillers, and Applied Terminal Systems business units. As part of the centralized Model-Based Engineering (MBE) department, this individual will focus on creating scalable frameworks, reusable modeling assets, and simulation workflows that accelerate the adoption of model-based controls throughout the organization. This role is primarily responsible for developing simulation infrastructure, teaching and mentoring engineering teams on model-based controls methods, and supporting the integration of simulation assets into Software-in-the-Loop (SiL), Model-in-the-Loop (MiL), and Hardware-in-the-Loop (HiL) environments. The ideal candidate will have strong expertise in control systems theory, simulation model development, embedded code generation workflows, and experience working across functional teams to promote model reuse and standardized control development processes. Come be a part of an exciting journey at Daikin Applied, where innovation and excellence drive our every endeavor!

Requirements

Currently enrolled M.S. or Ph.D. student in Mechanical Engineering, Electrical Engineering, Architectural Engineering, Controls Engineering, or a closely related field.
Academic or research focus in building automation, building energy modeling, HVAC systems, or advanced control methods.
Proficient in C++ and MATLAB/Simulink, including control system design toolboxes and embedded code generation.
Exposure in Stateflow and state charts for modeling control logic and state machine behaviors.
Willingness to work with Systems and Product Engineers to develop formal controls requirements and architectures
Understanding of control systems theory, including dynamic system response and PID tuning methodologies.
Exposure to simulation-based validation using SiL, MiL, and HiL environments and FMU integration.
Knowledge of Azure DevOps, Git version control, and automated build pipelines.
Knowledge of electrical schematics and control system instrumentation.
Exposure in the use of sensors and instrumentation including RTDs, thermocouples, pressure transducers, flow meters, and data acquisition systems.
Excellent verbal and written communication skills with the ability to work effectively across laboratory, design, product, and marketing teams.
Familiarity with Agile development processes.

Nice To Haves

Master’s degree in Engineering from an ABET-accredited institution (preferred).
Understanding of HVAC systems and components.
Experience with Linux-based programmable controllers and PLC programming (Functional Control Blocks and Structured Text).
Background in advanced control strategies including Model Predictive Control, Adaptive Control, and AI/ML control techniques.
Coursework or practical knowledge in measurement systems, heat transfer, thermodynamics, fluid mechanics, machine design, and strength of materials.
Programming experience beyond C++

Responsibilities

Develop and maintain tools, methods, and frameworks that enable scalable model-based controls development using MATLAB/Simulink, Stateflow, and Functional Mockup Units (FMUs).
Facilitate the deployment and integration of SiL, MiL, and HiL simulation environments to support accelerated control system development and validation across multiple business units.
Collaborate with the Principal Model-Based Controls Engineer to define and promote modeling standards, reusable control architectures, and validation workflows.
Teach and mentor controls engineering teams on the application of model-based controls methods, tools, and best practices.
Work with internal stakeholders to identify barriers to simulation adoption and provide technical solutions that improve workflow efficiency.
Develop and document standard modeling practices, including guidelines for simulation asset creation, model traceability, and governance.
Support prototype development and hardware validation activities through simulation-guided controls testing.
Investigate advanced control methods such as Model Predictive Control (MPC), Adaptive Control, and AI/ML-based control strategies for future tool development initiatives.
Manage software development activities related to controls tools using Azure DevOps, Git version control, and automated build pipelines.
Provide technical support for integrating model-based controls methods into new product development phase-gate processes.