Wifi HW intern

Description About Ceva Ceva is at the forefront of the Smart Edge revolution, with innovative state-of-the-art Silicon and Software solutions that enable products to Connect, Sense and Infer. Within the Wireless Internet of Things (WIoT) Business Unit, we are offering you a unique opportunity to shape the future of connected devices. Our advanced wireless technologies, including Bluetooth, Wi-Fi UWB, and 5G Cellular IoT, are integrated into over a Billion devices annually, driving innovation across industries. About the job Battery life is often the difference between a product users love and a product they abandon. For connected devices, battery life depends on hardware architecture, embedded software, network traffic, WiFi/Bluetooth coexistence and operating-system activity. This internship focuses on measuring, understanding and optimizing the energy profile of a complete WiFi IP under realistic conditions. You will work across Verilog-based digital design, embedded C software and WiFi validation, using automated data analysis to correlate measurements, logs and network events. In practical terms, the internship will be organized into several phases: Analyze power and data Characterize WiFi use cases by means of simulations across active, idle and low-power states. Correlate power profiles with firmware logs, RTL behavior and network events. Find optimization opportunities Identify unnecessary wakeups, background traffic and inefficient scheduling decisions. Build the measurement framework Set up synchronized power measurements, traffic generation and event logging. Create repeatable scenarios representative of real products and use cases. Requirements • Final-year engineering school or Master's degree student. • Curious about embedded systems and wireless technologies • Knowledge of digital design and hardware-description languages such as Verilog or SystemVerilog. • Familiar with Linux environments. • Interest in automation and data analysis to extract patterns and insights from logs, traces and measurement results. Python and/or AI-tools will be used. • Setting up and troubleshooting test setups. • Duration: 6 months • Start date: Early 2027