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expertise in optimisation; Computer Science, with expertise in design and analysis of algorithms and high-performance (GPU) computing; Industrial and Systems Engineering, with AI in process mapping and Conops
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Demonstrable ability in the use of multivariate statistics and state-of-the-art emulation (including physics-informed machine learning and neural operators) C2 Practical skills in computational inference
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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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discovery. Programming and Engineering: Strong Python skills (PyTorch / JAX / TensorFlow); comfortable with HPC and GPU workflows, modern MLOps, and reproducible computational pipelines. Agentic and
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that can better utilise distributed computing resources while reducing energy overheads and supporting more sustainable AI infrastructure. The successful candidate will have the opportunity to work on real
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addition to the pan-university Hamilton GPU resource (8 NVIDIA H200 NVL) which both complement our departmental NVIDIA CUDA Compute Cluster (80+ GPUs up to NVIDIA A100) to cater for the increasing GPU compute demands
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program called ENMED. This program was established to transform healthcare through translational interdisciplinary research, the development of medical technologies, and the development and training
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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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platforms (GPU/accelerated workloads): capacity planning/quotas, cluster or managed compute configuration, distributed training concepts, performance tuning, and chargeback/showback in cloud environments.
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, MIG, node affinity). Experience optimizing GPU utilization, memory management, and cost efficiency for compute-intensive workloads. Preferred Competencies Ability to collaborate and interact effectively