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results. Machine Learning skills to automise comparison process. Unbiased approach to different theoretical models. Experience in HPC system usage and parallel/distributed computing. Knowledge in GPU-based
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this, these simulations need to be massively parallelized. The objective of this thesis is to implement and evaluate different contingency parallelization approaches using our group's computational infrastructure
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skills and experience with numerical modeling and particle-based methods Interest in working closely with experimentalists Excellent written and spoken English skills Experience with parallel programming
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in geophysics, physics, geoscience, computational geoscience, or related natural sciences with an overall grade of at least good Experience in programming (e.g., matlab, phyton, C/C++) and parallel
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therapies, cell programming and repair, bioengineering, and computational health. Through this research, we build the foundations for medical innovation. Together with our partners, we seek to accelerate
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Center for Computational Neurosciences Berlin Medical Neurosciences International Graduate Programme Collaborative Research Center 1315 Collaborative Research Center/Transregio 384 Teaching language