54 algorithm-development-"St"-"St" Postdoctoral positions at Oak Ridge National Laboratory in United States
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Requisition Id 15472 Overview: We are seeking a Postdoctoral Research Associate who will contribute to the development and implementation of novel tensor network algorithms and their combination
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Scattering Division (NSD), the Instrument Development group in the Neutron Technology Division (both part of the Neutron Sciences Directorate at Oak Ridge National Laboratory (ORNL), and the Neutron and X
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computations relevant to the development of strategic nuclear performance codes for nuclear reactors. This position resides in the Radiation Effects and Microstructural Analysis Group (REMAG) in the Materials in
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advanced many-body methods, high-performance computing, and machine learning approaches. The successful candidate will play a leading role in developing computational methods and high-performance algorithms
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learning algorithms in PyTorch. Expertise in object-oriented programming, and scripting languages. Parallel algorithm and software development using the message-passing interface (MPI), particularly as
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scientific data Major Duties/Responsibilities: Design and implement advanced AI architectures and workflows for imaging and spatiotemporal data. Develop efficient and scalable training algorithms
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leading peer-reviewed journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration
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research associate position in AI for science. The Learning Systems Group seeks a postdoctoral researcher specializing in federated learning and privacy-preservation algorithms. The successful candidate will
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industrial imaging data. You will directly contribute to developing and deploying algorithms for multi-modal tomography (X-ray, neutron, and electron), advancing methods for non-destructive evaluation (NDE
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. Eventually, we aim to map these algorithms on to energy-efficient emerging devices. In addition, you may also explore applying LLMs to drive multimodal models in scientific domains towards deep reasoning. As a