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commonly used on Unix systems. Additional languages or experience with libraries for utilizing GPU hardware efficiently, e.g., CUDA, are a plus. Experience in AI programming with, e.g., PyTorch(-DDP
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Selectris energy filter and Falcon 4i. The Crick Institute has excellent High Performance Computing resources, dedicated high-speed data storage and CPU and GPU clusters. In collaboration with the Cryo-EM
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workflows, FAISS/embedding retrieval, LLM-based parsing, RAG-style pipeline, and GPU/HPC training. Familiarity with 3D data processing or willingness to learn quickly. Publications, thesis work
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-specialists E3 Experience handling large image datasets E4 Experience with HPC, GPU computing, or cloud-based computational workflows. E5 Experience in preparing analysis and presentation of data to publication
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: Experience in real-time simulation hardware like Opal-RT and RTDS. Experience with software development. Experience with use of DSPs, FPGAs, advanced computing (e.g., GPUs, QPUs). Excellent written and oral
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NVIDIA GPU nodes. Additionally, The CSM maintains enterprise computing infrastructure consisting of 20+ servers/devices. This includes various storage devices (TrueNAS, Synology), web servers and Windows
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Storage Scale) HPC environments and job scheduling systems AI workloads and GPU infrastructure Containers and orchestration (Docker, Kubernetes) Infrastructure as Code and DevOps practices What We Offer We
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resources to support your work (e.g., CAD tools, GPU servers, wet lab space) Research with impact – we are directly addressing the needs of multiple local stakeholders which are representative of the global
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Your profile: Preferably a doctoral degree, but MSc are also encouraged to apply Expert knowledge in one or several of the following High Performance Computing GPU computing Array Computing with JAX A
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physics, mathematics or any related field. What we offer State of the art on-site high performance/GPU compute facilities Competitive research in an inspiring, world-class environment A wide range of offers