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. This position offers an exciting opportunity to work at the intersection of HPC and AI, addressing critical communication bottlenecks and optimizing network interconnects for large-scale distributed systems
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We invite applications for a Postdoctoral Appointee to contribute to a growing research program in process systems modeling and optimization for clean energy, critical materials, and advanced
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algorithms to develop cybersecurity, optimization, and control solutions for real-world grid applications. Candidates will be required to work in at least 4 of the following areas: Build, simulate, and
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deployment, monitoring, and optimization of complex scientific data streaming workflows for current and future production infrastructures. The project will involve close collaboration with a team of systems
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-micron resolution of entire organs demands optimized data pipelines and methods to handle and visualize the resulting datasets. Additionally, beamline hardware must be optimized to ensure the highest data
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for deployment on large-scale computing resources, such as high-performance computers (e.g., Perlmutter, Aurora, etc.). This includes tasks such as automating model design, optimizing hyperparameters, and training
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presentations for group meetings. Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field in Chemistry, Chemical or Mechanical Engineering, Materials Science, or a related
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modeling tools to develop and optimize new processes and equipment designs using high-performance computing Analyze data, prepare manuscripts for submission to peer-reviewed publications, prepare technical
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algorithm development in conjunction with extensive applications in the fields of nanoscience and energy-related materials. Position Requirements a PhD in physics, or closely related field. Degree must have
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resulting from the deployment of new technologies. If you are passionate about sustainable energy solutions and optimizing supply chains for a more energy-secure future, we invite you to apply