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within a multi-disciplinary research environment consisting of computational scientists, applied mathematicians, and computer scientists to link models and algorithms with high-performance computing
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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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security challenges. CSMD delivers fundamental and applied research capabilities in a wide range of areas, including applied mathematics and computer science, decision science, discrete algorithms
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, high-performance computing (HPC), and computational sciences. Major Duties/Responsibilities: Participate in: (1) design and implementation of scalable DL algorithms for atomistic materials modeling
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computed tomography (CT) reconstruction, including sparse-view and limited-angle algorithms, and the application of advanced machine learning (ML) and computational imaging methods to scientific and
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across diverse clients. You will use Frontier's computational power to scale and validate these privacy-preserving algorithms, enabling breakthroughs across energy and image modeling domains. You will also
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that accelerate AI/ML when applied to large scientific data sets; Energy efficient physics-aware algorithms, capable of distributed learning on high performance and edge computing; The design of architectures
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to advanced computing resources. The MMD group is responsible for the design and development of numerical algorithms and analysis necessary for simulating and understanding complex, multi-scale systems
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algorithms, capable of distributed learning on high performance and edge computing; The design of architectures/models which accurately capture the complexities of the data, with robust estimates of confidence
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, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a travel allowance and access to advanced computing resources. The MMD group is responsible