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Field
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and/or image registration. Experience using high performance computing clusters/GPU based parallelisation. Experience solving diffusion or related equations by Monte Carlo methods. Knowledge of MRI
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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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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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skills (Python preferred), with familiarity in GPU or distributed computing environments. • Experience with biomedical or neuroimaging data is advantageous but not required. • Excellent analytical, writing
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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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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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communicate results clearly in writing and presentations. Desired Qualifications: Knowledge of GPU architecture and GPU programming. Interest or experience in distributed training on large scientific datasets
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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