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Field
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experimental data and workflows. The team drives innovation in algorithm design, GPU-accelerated computing, and quantum-ready methodologies applicable to complex scientific problems across the experimental
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Center for Devices and Radiological Health (CDRH) | Southern Md Facility, Maryland | United States | 7 days ago
approaches for automated medical devices (e.g., physiologic closed-loop controlled devices). Developing multi-spectral computational modeling tools using GPU-based processors to map light propagation
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samples. Optimize reconstruction algorithms for efficient large-scale 3D imaging, including high-performance and GPU-accelerated computing where appropriate. Design, optimize, and validate a refractive
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GPU acceleration, cloud computing, and distributed architectures, to enable efficient analysis of large-scale video datasets. Collaborate with clinical and academic collaborators, external partners
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research practices Experience training and deploying machine-learning models on GPU-based systems; familiarity with HPC environments is an advantage Interest in interdisciplinary research at the interface
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modern high performance computation facilities and parallel computing clusters (CPU and GPU). Excellent publication record and demonstrated conference presentation skills. Demonstrated ability to operate
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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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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