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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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-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
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programming. Strong oral and written communication skills. Excellent collaboration and teamwork abilities. Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork. Preferred
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independently as well as in collaboration with a multidisciplinary team. Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork. Desired: Any prior research experience in
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engineering controls such as gloveboxes or hoods is desired, but not mandatory. Strong interpersonal, written, and oral communication skills. Ability to model Argonne’s Core Values: Impact, Safety, Respect
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with a team. Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork. Preferred Knowledge, Skills, and Experience Experience in machine learning/deep learning methods