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Field
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contribute to the conceptual design of the database and oversee its implementation together with the Principal Investigator and the digital humanities engineer. In parallel, they will conduct original research
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manipulation Expertise in R and foundations of statistics Excellent communication skills and motivation to work collaboratively Ability to work independently and manage multiple projects in parallel Proficiency
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for social phenomena on massive parallel HPC systems and their applications together with applications of artificial intelligence under the guidance of TP Dr. Nobuyasu Ito. The main target is to develop models
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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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hydrodynamics and/or N-body simulations in the star and planet formation context Experience in the field with HPC system usage and parallel/distributed computing Knowledge in GPU-based programming would be
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maintaining the DataSpaces (https://dataspaces.sci.utah.edu/download/ ) project – a high-performance distributed data management framework designed for in-memory data staging and coordination in scientific
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Lab researches on a variety of computer systems topics including HPC resilience, data center power management, large-scale job scheduling and performance tuning, parallel storage systems and scientific
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support to the Head of Division on this topic. You are encouraged to visit the ESA website: https://www.esa.int/ Field(s) of activity/research for the traineeship Your tasks and responsibilities will be