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software that allow time-evolving models of complex systems to be calibrated against sparse, indirect, and uncertain observations. The group develops and maintains an open-source Python framework
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Requisition Id 17070 Overview: We are seeking a Postdoctoral Research Associate who will use multiscale modeling and simulation to develop probabilistic lifting frameworks for high-temperature
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into closed-loop control frameworks Test and validate control algorithms through simulation, hardware-in-the-loop testing, and/or physical testbeds Apply machine learning techniques to predict thermal system
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planning principles and frameworks that can be applied to various urban environments. Monitor and evaluate multi-energy-system integration solutions to ensure they comply with regulations and standards
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architectural models, system-level simulators, and performance modeling frameworks for QHPC systems, capturing relevant characteristics of quantum processing units, classical HPC resources, interconnects, system
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/ML frameworks. Experience with analyzing large, heterogeneous environmental, geospatial, remote-sensing, or time-series datasets. A strong record of scholarly productivity, as demonstrated by peer
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Requisition Id 16715 Overview: We are seeking a Postdoctoral Research Associate who will use multiscale modeling and simulation to develop probabilistic lifing frameworks for high-temperature alloys
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Language Models (LLMs). Distributed Machine Learning: Specialization in data parallelism, model-parallelism, and collective communication strategies in large-scale environments. Proficiency in frameworks
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compilers and runtimes can unify classical, quantum, and analog execution models under a shared optimization framework. Basic Qualifications: Ph.D. in Computer Science, Computer Engineering, or a closely
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frameworks linking molecular interactions to cellular and network-level behavior (e.g. protein-protein interaction, PPI, network analysis) Optimize simulation codes and workflows for leadership-class HPC