2027 Internship - Systems Engineering - Power & Control

Cirrus Venture Labs (CVL) is Cirrus Logic's technology accelerator, focused on developing disruptive, scalable, and monetizable innovations that solve high-impact industry problems. Our mission is to accelerate the introduction of foundational technologies and silicon-centric business models that enable Cirrus Logic to expand into new markets and product categories.

As a Graduate Systems Engineering Intern - Power & Control, you will work alongside experienced engineers, Innovation Managers, and technical architects to explore and prototype next-generation technologies across power electronics, motor control, and intelligent physical systems.

You will apply advanced academic knowledge to real-world engineering challenges through system modeling, simulation, hardware development, and experimental validation. We are particularly interested in candidates who combine strong fundamentals in physical systems with practical experience or curiosity in applying machine learning and modern AI tools to accelerate engineering discovery and prototyping.

This role offers an opportunity to contribute directly to early-stage technology initiatives, collaborate with external ecosystem partners, and gain exposure to the technical and commercial considerations that shape new semiconductor technologies and businesses.

Responsibilites

• System Modeling & Simulation: Develop system-level models using MATLAB, Simulink, Simscape, and related tools to analyze electrical, mechanical, and control system behavior. Evaluate system dynamics, stability, transient response, efficiency, and performance tradeoffs.
• Control Systems Development: Support the modeling and evaluation of linear and nonlinear control systems, including feedback control, state-space methods, motor control techniques, and advanced control algorithms. Explore opportunities for adaptive, predictive, and ML-augmented control.
• Power Electronics & Distribution: Analyze isolated and non-isolated power conversion topologies, power distribution architectures, and associated electrical and thermal considerations. Support the evaluation of converter performance, control strategies, and system-level integration.
• Hardware Design & Prototyping: Contribute to schematic capture, PCB design, component selection, and development of experimental hardware platforms. Participate in board bring-up, debugging, and rapid iteration of proof-of-concept systems.
• Lab Testing & Measurement: Perform hands-on testing and characterization using oscilloscopes, power analyzers, electronic loads, signal generators, and other laboratory instrumentation. Develop experimental setups and measurement methodologies to evaluate system performance.
• Simulation-to-Hardware Validation: Correlate analytical and simulation results with experimental measurements, investigate discrepancies, and refine system models and technical assumptions.
• Python & Data-Driven Engineering: Develop Python-based tools and scripts to automate simulations, process experimental data, visualize results, and support system characterization. Explore opportunities to incorporate machine learning into engineering analysis and experimentation.
• Technology Exploration: Research emerging technologies and engineering approaches in power electronics, motor control, advanced sensing, and intelligent physical systems. Help evaluate the feasibility and performance potential of new technical concepts.
• Cross-Functional Collaboration: Work closely with Innovation Managers, systems architects, and engineering teams to translate early-stage technical hypotheses into measurable experiments, engineering models, and proof-of-concept demonstrations.
• Ecosystem Partner Engagement: Participate in technical discussions and collaborative development activities with startups, technology vendors, universities, and research institutions. Support the evaluation and integration of emerging technologies from external partners.
• Customer Engagement: Collaborate with CVL team members in customer-facing technical discussions to understand application requirements, system constraints, and integration challenges. Help translate customer feedback into technical experiments and prototype requirements.
• Technical Communication: Document experimental findings, present technical results, and contribute to engineering reviews that inform architectural decisions and the progression of innovation initiatives.

Required Skills and Qualifications

• Educational Background: Currently pursuing a Master's or Ph.D. degree in Electrical Engineering, Computer Engineering, Control Systems, Power Electronics, or a related technical discipline.
• Technical Foundation: Strong academic foundation in electrical circuits, power electronics, system dynamics, and feedback control theory.
• Modeling & Simulation: Experience using MATLAB, Simulink, or comparable tools for system modeling, simulation, and analysis through academic research, coursework, or engineering projects.
• Control Systems: Understanding of linear and nonlinear control systems, stability analysis, and fundamental control techniques.
• Power Electronics: Familiarity with DC/DC conversion, switching power supplies, motor drives, and isolated or non-isolated power architectures.
• Hardware & Prototyping: Exposure to circuit design, schematic capture, PCB development, or hardware prototyping through academic research, coursework, or personal projects.
• Laboratory Skills: Experience with electronic test equipment and a strong interest in hands-on experimentation, measurement, and hardware debugging.
• Analytical Thinking: Strong problem-solving skills and the ability to apply first-principles engineering analysis to unfamiliar technical challenges.
• Collaboration & Communication: Ability to work effectively in multidisciplinary teams, communicate technical findings clearly, and operate in an exploratory research and development environment.

Preferred Skills and Qualifications

• Advanced Power & Control Systems: Graduate research or project experience in power electronics, motor drives, robotics, mechatronics, or cyber-physical systems.
• Motor Control Techniques: Familiarity with field-oriented control (FOC), sensorless control, model predictive control, or other advanced motor and actuator control techniques.
• Simulation Tools: Experience with LTspice, PLECS, PSIM, or similar circuit and power electronics simulation platforms.
• Hardware Development: Experience designing, assembling, bringing up, and debugging prototype PCBs or embedded hardware systems.
• Machine Learning & Python: Proficiency in Python for scientific computing, data analysis, and machine learning, including familiarity with libraries such as NumPy, SciPy, pandas, scikit-learn, PyTorch, or TensorFlow.
• ML Development Workflows: Familiarity with standard machine learning workflows, including data collection and preprocessing, feature engineering, model development, training, validation, benchmarking, and performance evaluation.
• ML for Physical Systems: Exposure to applying machine learning techniques to physical systems, including system identification, predictive modeling, anomaly detection, adaptive control, or optimization of power and electromechanical systems.
• Simulation & Data Integration: Experience using Python to automate simulations, process experimental data, and integrate analytical or physics-based models with data-driven approaches.
• AI-Assisted Engineering: Interest or experience leveraging modern AI development tools, coding assistants, and emerging agentic workflows to accelerate research, simulation, software development, and engineering experimentation.
• Embedded Systems & Programming: Experience with C/C++, embedded firmware development, microcontrollers, or real-time control implementation.
• External Collaboration: Experience participating in collaborative research projects involving industry partners, academic institutions, or multidisciplinary engineering teams.
• Entrepreneurial Mindset: Demonstrated curiosity, initiative, adaptability, and enthusiasm for exploring emerging technologies beyond a single engineering discipline. Comfortable navigating ambiguity, challenging assumptions, and rapidly experimenting with new ideas.