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frameworks such as Qiskit, CUDA-Q, PennyLane, Cirq, or equivalent platforms, and knowledge of quantum algorithms, quantum error correction, fault-tolerant computing, or quantum resource estimation. Experience
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application programming models such as CUDA, HIP, SYCL, OpenMP, Kokkos or Raja, vectorization; MPI; and one-sided asynchronous programming models. Experience in heterogeneous computing, developing and debugging
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distributed codes using MPI, OpenMP, CUDA, ROCm, and related HPC technologies while bridging theoretical AI models with real hardware constraints. Cross‑Paradigm Integration(new optional emphasis): Explore how
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system diagnostics. Experience with CUDA and deployment on NVIDIA edge-GPU platforms (Jetson Orin, Thor, or Spark). Experience calibrating and synchronizing LiDAR, IMU, camera, and wheel-odometry systems
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parallel programming with MPI, OpenMP, CUDA, HIP, and application-specific libraries Experience in developing, debugging, and profiling massively parallel codes Experience in multiple scattering methods