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straight-forward approaches typically lead to high execution divergence. With the introduction of advanced thread-synchronization features in the CUDA standard though, parallel patterns, such as producer
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of computer graphics fundamentals, numerical methods, and GPU/parallel computing concepts. Experience with at least one major deep learning framework (PyTorch preferred). Excellent problem-solving skills and
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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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Robotic Material via Wavelength-Division-Multiplexing (ColorfulAct)". ColorfulAct aims to establish the building blocks of physical intelligence parallel to nodes and connections to artificial intelligence
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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