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U.S. citizens are strongly encouraged to apply
The Adaptive Real-Time Systems Laboratory (ARTS-Lab) at the University of South Carolina invites applications for a fully funded Ph.D. research assistant position devoted to advancing artificial-intelligence and machine-learning methods on small, power-constrained hardware—edge AI—for real-time, in-situ manufacturing. Our group develops novel sensors for metal and polymer additive-manufacturing (AM) processes and couples them with embedded AI to detect, diagnose, and ultimately prevent defects as parts are being built. The successful candidate will help design secure sensing pipelines, craft physics-aware ML models that ingest vibration, acoustic, thermal, LiDAR, and event-camera streams, and deploy those models on microcontrollers, FPGAs (including side-channel-resistant and cyber-hardened implementations), and emerging neuromorphic chips. Cybersecurity is a first-class concern: you will explore lightweight encryption, anomaly detection, and trusted-execution primitives so that edge devices remain resilient against tampering and data exfiltration even in harsh industrial environments. Although
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