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Field
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developing and maintaining research software systems or web-based tools to support laboratory operations · Familiarity with Linux-based research computing environments and GPU-accelerated workflows Before
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skills. Other desirable criteria include: Image analysis experience, e.g. automated segmentation and/or image registration. Experience using high performance computing clusters/GPU based parallelisation
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programming and code porting on accelerators (FPGAs, GPUs) are being developed, as well as the development of RISC-V applications in scenarios where the use of open hardware is necessary. Another research topic
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their publications Experience programming GPUs with CUDA, SYCL, HIP or OpenMP Experience using and developing code with AMReX Experience in performance engineering to improve code scalability and reduce time-to
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required) Experience with machine learning / deep learning (PyTorch; model training; GPU workflows). Experience with Transformers / text embeddings / multimodal modeling (e.g., Hugging Face ecosystem
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and writing scientific code - Knowledge of at least one of the parallel programming paradigms (MPI, OpenMP, GPU) - Proficiency in both spoken and written English is essential (work will be carried out
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inhibitors with improved efficacy The project offers a highly interdisciplinary research environment spanning computational chemistry, cell biology, physics, and materials science. The work will leverage GPU
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biology results The project offers a highly interdisciplinary research environment spanning computational chemistry, neuroscience, molecular biology, and psychology. The work will leverage GPU computing
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 3 months ago
collaborators # Ability to set individual goals, self-structure and fulfill milestones # Parallel programming, ideally in C++ and with GPUs # Knowledge with Python # Excellent command of English (spoken and
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. Demonstrated experience developing and running computational tools for high-performance computing environment, including distributed parallelism for GPUs. Demonstrated experience in common scientific programming