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Field
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training activities Analysis of parallel scientific applications with respect to efficiency and scalability, in close collaboration with their developers Identification of optimisation potential, with focus
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Max Planck Institute for Intelligent Systems, Tübingen site, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | about 1 month ago
. Degree in Computer Science, IT, or a related field, or equivalent experience. Preferred: Familiarity with parallel computing, job schedulers, and high-speed networking. Experience with storage technologies
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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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experiment operation in 2028. Emphasis has to be put on the application of the software in real-time, making use of massive parallelism on CPU and/or on GPU. Your profile: From the applicant, we expect a
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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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currently studying computer science, mathematics or a related field Good skills in parallel programming using C++ Interest in the High Performance Computing field Ability to communicate with colleagues and
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parallel programming using C++ Basic understanding of the functionality of LLM Interest in the High Performance Computing field Ability to communicate with colleagues and discuss various problems in
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statistical/mathematical methods to analyse large data sets Comprehensive experience with HPC system usage, parallel/distributed computing, as well as diverse architectures and understanding of its impact on
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computer science (e.g. digital technology, chip design, computer architectures, hardware/software codesign, parallel architectures, operating systems). Innovating and improving teaching through new formats and
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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