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Collaborate with the software team to architect and prototype AI algorithms and solutions tailored for digital twin applications.
Design and implement simulations and Synthetic Data Generation workflows using Omniverse and NVIDIA Replicator.
Develop digital twin models for various industrial applications, such as: Simulating Autonomous Mobile Robots (AMRs) with cuOpt and ROS2 for fleet management.
Creating inspection workflows for simulated testing and quality improvement.
Building data-driven healthcare robotics simulations for training and data collection.
Optimize AI models and workflows for integration with Omniverse Replicator and associated tools to ensure real-time, high-fidelity simulation.
Collaborate with cross teams and partners to design, deploy, and improve simulation protocols tailored to specific operational needs.
Support customer engagements and internal teams by developing use cases for digital twins, bridging the gap between real-world operations and simulated environments.
MS or PhD candidate in Computer Science, Computer Engineering, Electrical Engineering, or a related field, graduating in 2025.
Specialization in Deep Learning, Digital Twin Technology, and Computer Vision.
Solid experience in developing digital twin models and simulations using NVIDIA Omniverse and Replicator SDK.
Hands-on experience on Synthetic Data Generation for inspection and Robot Operating System for robotics and fleet management.
Proficiency in optimizing AI algorithms and workflows for digital twin applications.
Familiarity with large language models (LLMs) and their integration with real-time digital twin systems.
Proficiency with deep learning frameworks like TensorFlow and PyTorch.
Experience with simulation platforms such as Omniverse, cuOpt, and related NVIDIA tools.
Strong programming skills in Python and C#.
Strong communication skills.
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