79 model-driven-development "Integreat Norwegian Centre for Knowledge driven Machine Learning" Postdoctoral positions at Oak Ridge National Laboratory
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mechanics, statistical modeling, and linear algebra Preferred Qualifications: Experience with density matrix renormalization group and tensor network algorithm development and application. Competency with
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computing), EMT simulations, and power electronics control. Major Duties/Responsibilities: Develop electromagnetic transient (EMT) models for transmission or distribution grids, synchronous generators, large
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. You will perform cutting-edge research on theory and modeling of dynamics in condensed matters. Major Duties/Responsibilities: Development of theoretical framework for driven and open quantum systems
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Research Associate to develop, scale, and apply artificial intelligence (AI) and deep learning (DL) models for power grid systems. The successful candidate will contribute to scalable AI workflows for grid
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Application-driven Composable Distributed Storage. The candidate will be able to make research contributions in understanding and efficient use of distributed data storage and I/O subsystems for High
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Requisition Id 16915 Overview: We are seeking a highly motivated postdoctoral researcher with a strong background in composite material development, technology development from lab to large scale
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transformative solutions to compelling problems in energy and security. Within ORNL, the Building Envelope Materials Research (BEMR) Group develops and deploys affordable, advanced, and resilient solutions
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Postdoctoral Research Associate- AI/ML Accelerated Theory Modeling & Simulation for Microelectronics
. Focus will largely be in developing and deploying such AI/ML algorithms, closely collaborating with theorists and experimentalists to realize physics- models and/or physics-aware ML-models that can bridge
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understanding of parallel application development techniques (parallel programming models, algorithms, and software) Preferred Qualifications: Experience in implementing ab initio simulation codes such as VASP
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of large-scale geospatial and time-series datasets. The candidate will develop and evaluate multimodal AI models to characterize vegetation and land-surface dynamics and quantify ecosystem responses and