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Requisition Id 15553 Overview: We are seeking a Postdoctoral researcher in data quality assessment and control and sensor network optimization who will focus on R&D of sensor network design. This
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(HPC), Artificial Intelligence (AI), and Quantum Computing (QC) paradigms to address next-generation scientific challenges. Workflow Benchmarking and Optimization: Design and implement robust
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, and optimize preprocessing pipelines using HPC resources, targeting scalable execution and automation. Collaborate with domain scientists to integrate pipelines into end-to-end AI workflows specific
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seeking to fill a Postdoctoral Research Associate position to work in the areas of environmental life cycle assessment (LCA), technoeconomic optimization; and industrial energy efficiency and production
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, the Frontier supercomputer, and collaborate with experts in machine learning, optimization, electric grid analytics, and image science. The successful candidate will design and implement differential privacy
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that advances the development of AI-ready scientific data, optimized workflows, and distributed intelligence across the computing continuum. In this role, you will have the opportunity to lead and contribute
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optimization, and application-driven performance analysis for HPC, scientific Artificial Intelligence (AI), and scientific edge computing. We are a leader in computational and computer science, with signature
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coding (Python) for building energy modeling and controls Preferred Qualifications: Expertise in modern optimal control techniques (e.g., AI based controls) High level of competence in coding and scripting
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. Implement and optimize data representations and pipelines suitable for machine learning and uncertainty quantification. Collaborate with AI/ML experts to design and test inference methods that map
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developing the technical basis for the first fusion nuclear facility and the position will involve several disciplines, with an intended focus on design, analysis, and optimization of fluid flows in tritium