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mathematics and engineering. The Interpretable Machine Learning Lab has dedicated access to high-performance CPU and GPU computing resources provided by Duke University’s Research Computing unit and state
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performing simulations with computational models of the Earth system on different levels of complexity scientific publication records appropriate for the experience level experience in scientific software
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be treated? • Which performance measures are the most appropriate ones for measuring the effectiveness of different programs? Although the position will make the key decisions with regard to the design
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performing simulations with computational models of the Earth system on different levels of complexity scientific publication records appropriate for the experience level experience in scientific software
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within the 2DPHYS and CAMD sections at DTU Physics as well as at DTU Compute and DTU Nanolab. Required qualifications Significant experience with theoretical and computational nanophotonics High level of
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coding experience with e.g. Python/Matlab/R Practical experience with High Performance Computing, and scientific programming and a willingness to learn to work with high-performing computing systems
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inland, short-sea, and high-seas shipping routes. The project seeks to deliver industry-relevant tools that enable optimal design and operation of greener vessels, backed by real-world demonstrations