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applications. HPC and orchestration of scientific data processing workflows. Parallel computing (GPU & CPU). good software engineering practices for scientific software (version control, testing, continuous
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targets an order-of-magnitude improvement in efficiency through parallelization, near-sensor processing, and heterogeneous architectures with specialized accelerators. chevron_right Working, teaching and
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and outbound prospects related to any outreach and sales activities for SNAI. Devise and implement sales formats enabling multiple prospects to engage with SNAI offerings in parallel (thematic events
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Background in high-performance computing (HPC) or cloud environments Comfortable working in Linux/Unix environments Advantageous qualifications: Development of parallel applications Strong Python knowledge
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multiphoton microscopy, you will explore the molecular and cellular mechanisms of foreign body reactions. In parallel, you will collaborate with engineers to design and test microgels with tunable surface
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such data; hands-on experience in scaling up and/or parallelizing codes on HPC systems using languages such as e.g., C/C++, Fortran, Python; solid knowledge of parallel programming models (e.g., MPI, OpenMP
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experience in developing software for scientific applications, data analysis, or real-time systems is desirable. Experience with parallel computing and optimization techniques for handling large datasets
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programming in Julia or a strong willingness to learn Strong English speaking and writing skills Able to work well in a team Heliosphere / plasma science, cosmic dust science, astrodynamics Parallel processing