56 software-defined-network-postdoc Postdoctoral positions at Oak Ridge National Laboratory
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(For postdocs, use [email protected] ) with the position title and number referenced in the subject line. Instructions to upload documents to your candidate profile: Login to your account via
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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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be expected to model prototypes of the fiber optic based sensors using standard Multiphysics software, perform out-of pile laboratory testing of the instruments in representative environments, and
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such as classifier free guided diffusion models, transformers with multi-headed attention, physics-informed neural networks, materials foundational models with multi-task learning, symbolic regression
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credential to maintain employment. Postdocs: Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before starting
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. Writing and communication skills and the ability to publish. Preferred Qualifications: Experience with Multiphysics software and simulations an asset. Previous experience with the development and
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interact closely with industry partners. These engagements will play a vital role in ensuring success of programs and the adoption by project sponsors, and in developing your network across academia and
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them sent to [email protected] (For postdocs, use [email protected] ) with the position title and number referenced in the subject line. Instructions to upload documents to your
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the My Documents section, select Add a Document Postdocs: Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before
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Requirements: The prospective candidate should be well-versed with deep neural networks, have experience working on PyTorch or similar DL frameworks, programming in Python (preferred), NLP packages and pipelines