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Senior Research Engineer, AI Wireless - Plano, United States - Samsung Research America
Description
Lab Summary:
The Standards & Mobility Innovation team is committed to developing technologies that enable ubiquitous access to information and provide immersive multimedia experiences for mobility users
Our research focuses on:
Wireless standards and technology including 5G/6G, Wi-Fi, FiRa/UWB, MPEG, AOM, CSA Matter, CSA ACWG, CCC, etc
RF & fast prototyping of 5G and IEEE 802 wireless systems and/or use cases
Multimedia standards and technology including VR, HDR, All-IP delivery
IoT standards and Smart Home connectivity/sensing technology
Position Summary:
Join SMI lab of Samsung Research America in Plano, TX to contribute to the development of Samsung's vision of next generation of wireless communication technology.
The candidate shall be responsible for developing, profiling and delivering algorithm, design specification and software for AI empowered wireless communication system.
Position Responsibilities:
Design next generation wireless communication products
Apply AI and machine learning for designing optimized wireless systems targeting different use-cases, and demonstrate improved performance
Create system specification based on the high-level concept including applying AI and machine learning for wireless systems
Integrate wireless system simulator with generic machine learning environments, and evaluate performance with AI-in-the-loop simulations or prototyping
Generate clear, organized technical reports and assist the development of related IPR
Required Skills:
Ph.
D. in Computer Science/Electrical Engineering/Computer Engineering or equivalent combination of education, training, and experience
The preferred candidate will have 1+ years of industry (or good match academic research) experience in an advanced technology development environment
Excellent working knowledge using Python and Python based ML modules such as Scikit-learn, Keras, Tensorflow, Keras-RL, PyTorch and Pandas libraries
Have prior experience implementing machine learning algorithms for solving challenging problems preferably in wireless communication system design
Hands-on experiencing integrating Python ML modules with wireless system simulators
Solid background in digital signal processing and wireless communication systems design and different components including digital filters, FFTs, synchronization, channel estimation, equalization, MIMO detection, error-correction codes, etc
Good understanding of RF system architecture, performance specification and measurement, RF/baseband interface
Familiar with 3GPP standards
Excellent verbal communication and technical writing skills
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