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single-mode and multimode semiconductor laser arrays Optimization and acceleration of existing simulation codes Parallel computing and high-performance computing (HPC) GPU acceleration, where
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interdisciplinary project; we are open to work with researchers with varying academic backgrounds. Those with experience in, for example, machine learning, high-performance computing, reconfigurable hardware, cloud
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principles and research data management. Experience with high-performance computing, cloud computing, GPU acceleration, or distributed data processing. Experience participating in international scientific
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-performance computing is an advantage Strong background in machine learning for image analysis and computer vision, ideally involving microscopy, time-lapse imaging, or other high-dimensional scientific
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additional programming languages is an advantage Experience with Linux/UNIX-based scientific computing environments and modern software development practices Experience with parallel computing and high
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Administrator (Senior Research Fellow) to oversee and optimize our High-Performance Computing (HPC) and distributed AI infrastructure. In this role, you will lead the architectural design and
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. CMSE centers around computational approaches, encompassing algorithm development, high-performance computing, scientific modeling, and data science. The department has an active research community
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. Significant experience using Python for high performance applications with libraries such as: Numpy, Numba, CuPy, and PyQtGraph Significant experience using C++ for numerical computing applications
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available datasets to interpret results in a robust biological context Ensure reproducibility, data management, and documentation of computational workflows in high-performance computing environments
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with researchers with varying academic backgrounds. Those with experience in, for example, machine learning, high-performance computing, reconfigurable hardware, cloud computing, compiler engineering