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Requisition Id 16602 Overview: We are seeking a Postdoctoral Researcher who will focus on conducting, coordinating, and reporting complex research assignments related to advanced thermal and energy
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incorporated into complex microelectronic and optoelectronic architectures, with particular emphasis on interfaces between two-dimensional and conventional semiconductor materials. This position resides in
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or program datasets. Proficiency in statistical programming and data analysis tools: R, Python, Stata, or SAS SQL/database management preferred. Ability to clean, harmonize, and analyze complex datasets from
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, engineering, computing, and environmental sciences to address complex scientific challenges and accelerate the translation of discoveries into real‑world solutions. As a Postdoctoral Research Associate, you
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, Pandas, SciPy, scikit-learn, PyTorch, TensorFlow) Experience developing and deploying machine learning or deep learning models Ability to present complex results to multidisciplinary teams, including
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systems. Research activities will address key challenges in AI for science, including surrogate modeling, uncertainty quantification, and multi-fidelity optimization for complex simulation workflows
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of complex biosystems. The successful candidate will also contribute to efforts that bridge molecular, cellular, and systems-level modeling, with growing relevance to emerging paradigms such as whole-cell
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such as quantum and analog computational models. You will explore how compilers, runtimes, and AI-driven agents can co-optimize complex architectures, reasoning across conventional processors (CPUs/GPUs
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data-model integration, leveraging the U.S. Department of Energy’s (DOE) Leadership-Class Computing Facilities to advance predictive understanding of complex environmental systems. Major Duties
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/Responsibilities: The successful candidate will be responsible for conducting, coordinating, and reporting complex research assignments related to energy conversion systems including: Design and develop experimental