Systems Engineering Intern (Nanotech and Sensing)
Texas Instruments
This Systems Engineering Intern role is within Kilby Labs, the central R&D organization of Texas Instruments (TI). The lab is chartered to develop novel and innovative technologies and strategies for new business opportunities, drive next generation, differentiated technologies for existing businesses and recruit top technical talent for TI.
In this Systems Engineering intern role, you will be exploring cutting edge applications of reinforcement learning (RL) in next generation mixed signal and sensing systems. You will apply state of the art RL techniques to solve challenging problems in control, signal processing, and system level efficiency optimization – spanning domains such as power conversion, sensing and signal beamforming. You will develop intelligent control and adaptation strategies that push the limits of performance, efficiency, and robustness beyond traditional approaches. What you will do:
Research and implement RL based algorithms for optimizing dynamic, multi-objective systems.
Develop simulation and hardware in the loop environments to evaluate and validate RL performance.
Benchmark RL results against conventional control and optimization techniques.
Collaborate with TI’s product and research teams to translate concepts into real silicon and system innovations.
Responsibilities
System Knowledge: Develop and apply system expertise in a given application area and design solutions using existing TI silicon devices (DSPs, MCUs, MPUs, analog components, etc.) as well as specify and develop new devices
Signal Processing: Develop algorithms to calibrate, intelligently operate and analyze sensor data, and provide desired excitation signals/results for a given application.
Hardware Design: Define data and control data paths, AFE hardware requirements for sensor and actuation interfaces to digital signal processing units (DSPs, MCUs, MPUs, etc) and work with board designers to develop prototype systems
System Simulations: Develop complete system simulations to validate the viability of a given solution, analyze system performance requirements and perform system tradeoff analysis
Prototyping: Develop a working prototype together with team members using TI product portfolio: DSP/MCU/MPU device + AFE + sensor to demonstrate solutions
Product Development: Work with team members to provide necessary collateral (simulations, software, schematics, test infrastructure, user guides, and performance results) to ensure a smooth transition from prototyping to product development
Intellectual Property: Generate relevant patents to protect TI position in the application space
Emerging Technologies: Monitor competitive landscape for performance benchmarks relative to competition and find new applications/opportunities using existing TI products or define future products
- Engineer your future. We empower our employees to truly own their career and development. Come collaborate with some of the smartest people in the world to shape the future of electronics.
- We're different by design. Diverse backgrounds and perspectives are what push innovation forward and what make TI stronger. We value each and every voice, and look forward to hearing yours. Meet the people of TI
- Benefits that benefit you. We offer competitive pay and benefits designed to help you and your family live your best life. Your well-being is important to us.
TI does not make recruiting or hiring decisions based on citizenship, immigration status or national origin. However, if TI determines that information access or export control restrictions based upon applicable laws and regulations would prohibit you from working in this position without first obtaining an export license, TI expressly reserves the right not to seek such a license for you and either offer you a different position that does not require an export license or decline to move forward with your employment.
Minimum Requirements
Currently pursuing PhD degree in Electrical Engineering, Electrical and Computer Engineering or related field with algorithm and signal processing/data analytics background and mixed signal hardware experience
Cumulative 3.0/4.0 GPA or higher
Preferred Qualifications:
Strong foundation in reinforcement learning, control theory or optimization algorithms.
Proven experience with embedded control, hardware in the loop, or real-time experimentation.
Proficiency in Python (e.g. PyTorch, stable-baselines), Matlab/Simulink.
Creative thinker with hands-on problem solving and data-driven experimentation skills.
Experience in resolving differences between simulation and real time prototype results to demonstrate value in proposed solution.
Experience in debugging HW/SW and delivering a prototype that meets requirements.
On-time delivery of solutions with high quality.
- Works well with others and can brainstorm potential solutions together