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for reproducible, efficient and scalable training and inference on parallel, distributed and GPU-accelerated computing systems Benchmark the developed approaches against established methods, assessing
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researcher Are you excited to help find and assess the most promising habitable exoplanets around solar-like magnetically active stars? Join us to build next‑generation GPU‑accelerated models of stellar
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promising habitable exoplanets around solar-like magnetically active stars? Join us to build next‑generation GPU‑accelerated models of stellar dynamos and connect them to exoplanet discovery and space
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benefits can be found at https://postdoc.hms.harvard.edu/guidelines . With this appointment, you are represented by the Harvard Academic Workers ( HAW ) – UAW for purposes of collective bargaining and
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benefits can be found at https://postdoc.hms.harvard.edu/guidelines . With this appointment, you are represented by the Harvard Academic Workers ( HAW ) – UAW for purposes of collective bargaining and
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benefits can be found at https://postdoc.hms.harvard.edu/guidelines . With this appointment, you are represented by the Harvard Academic Workers ( HAW ) – UAW for purposes of collective bargaining and
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health and welfare benefits. A supportive team environment that promotes collaboration and knowledge sharing. Access to world-class computational infrastructure, GPU-based computing environments, and
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Jülich supercomputers (GPU/CPU), or being combined with a practical modeling project. Your Profile You are currently enrolled in a Masters degree and are planning your thesis You are highly motivated
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infrastructure for deep learning, speech, and audio research, including Aalto University’s large-scale scientific computing cluster with CPU and GPU nodes, access to CSC’s national computing infrastructure
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, and audio research, including Aalto University’s large-scale scientific computing cluster with CPU and GPU nodes, access to CSC’s national computing infrastructure including LUMI, and the Aalto