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in computational modelling of additive manufacturing and develop high-performance GPU-based CFD solvers. Qualifications • With PhD degree • Strong research experience in
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Time (LSST). The Fellow will honor the legacy of Dr. Vera C. Rubin by conducting cutting-edge research using state-of-the-art computational infrastructure—specifically dedicated high-performance GPU
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-funded fellow, you will have early access to the Empire AI clusters, utilizing state-of-the-art GPU architectures to push the boundaries of structural biology. This position is a prestigious Empire AI
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) environments, GPU-enabled systems, and cloud-based resources for large-scale data analysis and model development. Using these rich data resources, we develop and apply advanced AI/ML methods to model tumor
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networks. Experience securing research funding, managing research programs, and building academic partnerships. Experience with embedded systems, FPGA/RTL, and RF technologies, and CUDA coding for GPU
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background in computer systems, GPU programming. Experience with CUDA, Triton, PyTorch, and LLM inference frameworks. Experience in research and good publication record. Track record first-author publications
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of algorithms and high-performance (GPU) computing; Industrial and Systems Engineering, with AI in process mapping and Conops design. With SUTD located next to the number #1-ranked airport in the world
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-performance computing environments and GPU computing. Proven experience in weather and climate models development and applications. Experience in machine learning, deep learning, or AI applications
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, TensorRT) Edge computing or embedded vision systems (e.g., NVIDIA Jetson Nano) Real-time processing and GPU acceleration Experience working on industry R&D projects Key Competencies Able to build and
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), numerical methods, and scientific software development. Proficiency in C/C++ and Python, with experience in HPC environments (e.g., MPI /OpenMP; GPU experience a plus). Record of peer-reviewed