We are seeking a highly motivated summer intern to support advanced R&D activities in intelligent and AI-enabled control systems for next-generation AI infrastructure. The intern will work closely with research engineers to develop and validate control strategies for multi-phase Vienna rectifier-based PSU architectures targeting high-efficiency, scalable, and fault-tolerant AI rack systems. The internship will emphasize AI-assisted control development, adaptive operational optimization, coordinated multi-phase control, and system-level modeling for advanced PSU architectures. The candidate will support simulation, Model-in-Loop (MIL) validation, data analysis, and prototype-oriented algorithm evaluation aimed at accelerating H 3-to-H 2 technology transition and strengthening the innovation and patent pipeline. Responsibilities Support development of AI/ ML-based control algorithms for advanced multi-phase PSU architectures and six-phase Vienna rectifier systems. Assist in development and validation of: Multi-phase coordinated control strategies Adaptive mode switching methods Dynamic phase reconfiguration techniques Load-aware intelligent power management algorithms Develop simulation models and reduced-order models. Perform Model-in-Loop (MIL) validation and controller performance evaluation. Analyze transient, steady-state, efficiency, thermal, and fault-response behavior of advanced PSU systems. Generate and organize experimental/simulation datasets for AI-driven control training and validation. Support prototype-oriented feasibility studies and design validation activities. Collaborate with cross-functional R&D teams working on H 3 innovation initiatives for AI infrastructure and next-generation technologies. Qualifications Required Qualifications Pursuing MS or PhD in: Electrical Engineering Mechanical Engineering Control Systems Computer Engineering Mechatronics Related engineering discipline Familiarity with simulation/modeling tools such as: MATLAB/ Simulink Basic programming experience in: Python MATLAB C/ C Strong analytical, problem-solving, and technical communication skills. Preferred Qualifications Experience with: AI/ ML control development Digital control implementation AI/ ML-based control techniques Reinforcement learning or adaptive control Exposure to: Model-in-Loop (MIL) Hardware-in-Loop (HIL) Digital twin concepts AI infrastructure or data center power systems Interest in advanced R&D, innovation, and patent generation activities. Prior research publications or hands-on laboratory experience in power electronics or intelligent control systems is a plus. Expected Outcomes Accelerated development of AI-driven control frameworks for AI rack PS - Us. Validated models and datasets supporting intelligent controller development. Improved readiness for H 3 ? H 2 technology transition. Enhanced invention disclosure and patent generation pipeline. Faster evaluation of adaptive multi-phase architectures and intelligent power delivery strategies. The successful candidate will embrace Vertiv’s Core Principals & Behaviors to help execute our Strategic Priorities.