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competitive residency program with 25 positions, we offer 9 fellowships and participate in numerous graduate school and the MD/PhD program of the CU School of Medicine. Why work for the University
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following areas: Machine Learning, Deep Learning, Reinforcement Learning, Data Mining; Programming; Parallel programming and High-Performance; Computing; Scientific computing, Numerical methods, and Numerical
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computing, such as Python and C. Training in one or several of the following areas: computational physics, numerical methods, signal processing, statistical inference or scientific data analysis. Ability
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& Engineering, or a closely related engineering discipline, with strong emphasis on high-fidelity CFD Experience in advanced CFD solver development, algorithm improvement, and numerical methods for highly coupled
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), with project number 101324772, within program HORIZON-JU-ER. Application procedure Are you interested in this vacancy? Please … Where to apply Website https://www.academictransfer.com/en/jobs/362701/phd
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leading research groups at both NTNU and SINTEF in scientific computing, numerical methods, and AI. Stimulating work in a strong national and international professional environment. Career guidance and
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. Experience in numerical methods and CFD development using mesh-based scientific codes. Expertise in the lattice Boltzmann method (LBM) as evidenced by their publications High performance computing (HPC
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program with 25 positions, we offer 9 fellowships and participate in numerous graduate school and the MD/PhD program of the CU School of Medicine. Our faculty and staff are diverse and gender balanced
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the development and application of industrial ecology methods, as well as the use of large data sets and scientific computing in industrial ecology. We focus on understanding resource use and
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learning Demonstrated expertise in software and algorithm development, computational methods, data analysis, modeling, machine learning, high-performance and parallel computing, or scientific simulation