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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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-edge Machine Learning applications on the Exascale computer JUPITER. Your work will include: Developing, implementing, and refining ML techniques suited for the largest scale Parallelizing model training
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research projects. In parallel, they participate in the comprehensive BIGS DrugS education programme, which includes workshops, lectures, colloquia and symposia. Mentoring is performed by two experienced
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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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are expected. Knowledge in parallel programming is desirable. Prior knowledge in differential-algebraic equations, Gaussian processes or kernel based methods is a plus; programming experience in Python or C/C
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Possibility of finding part-time employment Fellowship students are allowed to work parallel to their studies for a limited amount of working hours and a limited salary. Accommodation A simple way to find a
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timetable for the four-year project to be submitted to DAAD. Development of relevant analytical methods and setting up of required laboratory equipment will be conducted in parallel. Execution of the research