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Field
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for image segmentation and image analysis on the GPU cluster at EnMed (Pettigrew lab) Document the pipeline implementation for ready application by the EnMed students. Assists with data systems management and
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, virtualisation technologies and performance optimisation. Hardware acceleration technologies and modern compute architectures, including GPUs and high-performance networking technologies. Programming and scripting
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. Administration and Operations: Partner with IT teams to administer, configure, monitor, and maintain research computing environments, including IBM zSystems, Linux-based servers, GPU and accelerator resources
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-throughput processing. Enhance the computational efficiency of compute environments by optimizing resource allocation (including CPU/GPU utilization), parallelizing data pipelines, and resolving processing
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decentralised AI training systems using real-world workloads, GPU infrastructure, and industry-relevant deployment scenarios; and Generate open-source frameworks, algorithms, benchmarks, and research outputs
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Max-Planck-Institut für Struktur und Dynamik der Materie | Hamburg, Hamburg | Germany | 3 months ago
computing technologies and accelerator (GPU) computing. Familiarity with scientific software toolchains, including compilers, numerical libraries, parallel programming frameworks, and scientific software
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infrastructure, including GPU-based systems. Also of importance are: Demonstrated teaching proficiency Type of employment: The position is fixed-term for four years. During the period of employment, an Associate
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departmental CPU/GPU computing resources and Imperial’s Research Computing Service. • A vibrant, interdisciplinary research culture, with partnerships such as the CNRS–Imperial de Moivre Laboratory
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Max Planck Institute for the Structure and Dynamics of Matter, Hamburg | Hamburg, Hamburg | Germany | 3 months ago
Qualifications Experience in Linux system administration and HPC system administration. Experience with parallel computing technologies and accelerator (GPU) computing. Familiarity with scientific software
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Assistant Professor Position in Transient Electromagnetic Signal Processing, Modelling and Inversion
field data acquisition, processing, and interpretation. * Strong programming skills. Advanced Python programming is mandatory; experience with PyTorch, GPU-implementations, or other high-performance