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system) and disordered materials is also desirable. The project will involve developing autonomous materials discovery workflows on HPC platforms that can learn structure-chemistry-property relationship in
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. This position resides in the Multiscale Modeling and Materials by Design (M2MD) Group within the Materials Science and Technology Division (MSTD), Physical Sciences Directorate (PSD) at Oak Ridge National
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relationships via digital manufacturing practices Basic experience with AI/ML techniques Publish research in peer reviewed journals and conferences Support R&D staff members on their projects General support of
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: Collaborate with internal and external researchers on a variety of data and storage related research projects for use cases in HPC, scientific AI, and scientific edge computing. I/O and storage performance
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, including: Surrogate models or learned potentials Generative models for biomolecular design Representation learning for biomolecular systems Familiarity with protein–protein interaction (PPI) networks
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carlo), as well as experience in developing and/or applying advanced AI/ML methods to accelerate materials discovery. The project will involve integrating such theory-informed AI-models for creating
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Postdoctoral Research Associate- AI/ML Accelerated Theory Modeling & Simulation for Microelectronics
that can incorporate multi-scale computational simulations to aid with data fusion across multiple modalities of experiments with the final goal of discovering novel materials phenomena or even new materials