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Field
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scientific computing, image analysis and research infrastructures, you will collaborate closely with scientists, software engineers, beamline scientists and computing specialists across the European
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Qualifications Strong expertise in agentic scientific machine-learning, advanced analysis of fluid mechanics, dusty plasmas, scientific computing, and multi-scale modeling methods are preferred
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(scientific Python, PyTorch) with solid experience in scientific computing, reproducible software development, and modern software engineering practices; familiarity with C++, Linux, and high
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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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analysis, scientific computing, PDE together with research experience in scientific machine learning, are particularly encouraged to apply. Required Application Materials Applications will be reviewed
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of the appointment. Preferred Qualifications: Candidates with strong backgrounds in kinetic equation, numerical analysis, scientific computing, PDE together with research experience in scientific
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computing. ScaleQ will develop bulk and integrated photonic systems for measurement-based Gaussian boson sampling (MBGBS), using squeezed light, multimode entanglement and photonic integrated circuits to
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The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing
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Information Technology section at DTU Physics. You will lead one of three experimental projects in quantum opto-acoustics, continuous-variable (CV) quantum communication, or CV quantum computing, working in an
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geometry, number theory, data. * Qin Li: Scientific computing, machine learning, inverse problems. * Hanbaek Lyu: Combinatorics, probability, optimization, and machine learning. * Laurentiu Maxim