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learning methods and frameworks especially applied to physical science problems. Experience with x-ray data analysis and/or modeling, such as crystallography, diffraction, or spectroscopy data analysis and
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models, including training, fine-tuning and inferencing, at scale. It will help us better understand and improve DAOS to meet the needs of AI-driven science applications. We expect the postdoc to help
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., transient absorption and emission), including laser operation, optical alignment, detector interfacing, and data analysis Excellent written and verbal communication skills Ability to model Argonne’s core
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, and optimize for energy efficiency HPC applications and high performance data stream analytics workloads. Use of novel accelerator designs, and automatic methods to model/predict how performance would
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, and spatial transcriptomics. Key responsibilities include: Developing AI/ML methods for image alignment across modalities Automated feature detection Predictive modeling of vascularization patterns
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techniques to enable multimodal online monitoring of chemical and radiochemical separations processes Acquire fundamental data relevant to chemical separations in support of related modeling efforts Analyze
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in GPU programming one or more parallel computing models, including SYCL, CUDA, HIP, or OpenMP Experience with scientific computing and software development on HPC systems Ability to conduct
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Applications are invited for post-doctoral positions in the Cosmological Physics and Advanced Computing Group (CPAC) Group in Argonne National Lab. Research at CPAC covers theory, modeling
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-ion battery operation, cathode materials, and degradation mechanisms Excellent written and oral communication skills and the ability to work collaboratively in a team environment Ability to model
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glovebox operation. Demonstrated problem-solving and innovation skills. Organizational and critical thinking skills. Able to prioritize and manage time effectively. Ability to model Argonne’s core values of