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Field
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made at the Postdoctoral Research Associate rank. The AI Postdoctoral Research Fellow will have access to the AI Lab GPU cluster (300 H100s). Candidates should have recently received or be about to
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for embedded and GPU platforms. Collaborate with ARSPECTRA engineers and surgeons to create a complete AR guidance pipeline : tracking, SLAM, gaze, user interface Your profile PhD in machine learning
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developing machine learning surrogates and emulators for dynamical systems. Proficiency in managing large datasets and training with GPU-enabled computing resources. Expertise in numerical optimization and
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-of-the-art compute and GPU infrastructure, including H100 and B300 GPU clusters. Innovation: The opportunity to apply a recently published, "proof-of-concept" method for synthetic enhancer design to a critical
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distributed computing for EMT simulations. • Experience with software development in Python, C++, or other programming languages. • Familiarity with GPU acceleration of numerical solvers, parallel sparse
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-on experience developing generative models Is highly proficient in PyTorch and/or JAX Has experience training large-scale neural networks on HPC or GPU clusters Has experience with representation learning and
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transformer architectures (e.g., ViT/TimeSformer, CLIP/BLIP or similar) in PyTorch, including scalable training on GPUs and reproducible experimentation. Demonstrated experience building explainable models (e.g
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-on experience developing generative models Is highly proficient in PyTorch and/or JAX Has experience training large-scale neural networks on HPC or GPU clusters Has experience with representation learning and
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multiphase flows Your tasks Develop and extend the in-house GPU-accelerated multiphase Lattice Boltzmann (LBM) code for DNS-grade boiling multiphase flow related to nuclear reactor operation, including bubble
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chemistry and experience with quantum chemistry packages (e.g., Molpro, NWChem) Strong skills in developing and implementing computational and numerical methods; familiarity with parallel computing on CPU/GPU