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pretraining and fine-tuning is a plus · Experience with multi- GPU or distributed training is a plus · Ability to work independently as well as part of an interdisciplinary team in a fast-paced
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interdisciplinary team and supported by cutting-edge HPC and GPU infrastructure, you will contribute to internationally leading research, publish in high-impact journals and present your work at
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-image registration , high-performance computing, or GPU-based computation. Familiarity with machine-learning or deep-learning methods for medical-image segmentation. Previous experience in thermal
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will leverage GPU computing on the LUMI supercomputer, one of Europe’s fastest, to perform state-of-the-art molecular simulations. The position includes secondments to industry partners for
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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 9 hours ago
training. Multi-scale imaging: micro-CT, SEM, FIB-SEM, or synchrotron data handling. HDF5 / Zarr data schemas and GPU-accelerated volumetric processing. Published work in generative models, synthetic
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. Experience or training and deploying models on Graphics Processing Unit ( GPU ) hardware. Working Conditions Needs to be able to successfully perform all required duties. Office/research environment
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quantitative data analysis, statistical reasoning, validation and interpretation of results. Experience with FPGA, GPU or accelerator technologies. Familiarity with high performance or embedded
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and graduate research assistants, and presenting at design reviews and project milestones. Conducts benchmarking and performance evaluation of LLM serving and agentic workflows on high-performance GPU
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and supported by cutting-edge HPC and GPU infrastructure, you will contribute to internationally leading research, publish in high-impact journals and present your work at major scientific
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UK's most ambitious investments in fundamental AI research. What about computing power? Well, BOLD also has access to national compute resources (3M GPU hours on Isambard for the first 1.5 years) and