21 evolutionary-algorithm Postdoctoral research jobs at Oak Ridge National Laboratory in United States
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Requisition Id 15721 Overview: We are seeking a Postdoctoral Research Associate who will contribute to the development and implementation of novel quantum algorithms for materials simulation, with
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Requisition Id 16262 Overview: We are seeking a postdoctoral researcher to work at the intersection of tensor networks, quantum algorithms, scientific computing, topological physics, and quantum
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and numerical algorithms for modeling and simulation of nuclear systems. Computational Nuclear Engineers within the RTHPCM group will work with group, section, and division members and external
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-class S&T products for sensitive national security missions. The selected candidate will support research efforts in signal processing and analysis, with an emphasis on the development of novel algorithms
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include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a travel allowance and access to advanced
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scalability of simulation workflows via: Parallelization and performance engineering GPU/accelerator optimization Algorithmic innovation Experience applying machine learning or AI to molecular simulation
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performance modeling, static analysis, or PIM/heterogeneous architecture research. Knowledge of large-scale scientific computing applications and algorithms (sparse linear system solvers, dense matrix
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Analytics (MSA) Group in the Manufacturing Science Division (MSD), Energy Science and Technology Directorate (ESTD), at Oak Ridge National Laboratory (ORNL). Major Duties/Responsibilities: Develop algorithms
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AI/ML, with a focus on multimodal learning, computer vision, and scientific machine learning Develop novel algorithms and architectures for tasks such as multimodal retrieval, reasoning over complex
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for unstructured meshes and/or finite element methods. Experience with CFD discretization techniques for unstructured meshes and/or finite elements with an emphasis on highly scalable algorithms for exascale HPC