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of advanced materials. Research efforts will include the application of density functional theory packages and in-house codes, and the development of supplemental numerical tools, to describe
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to optimize utility of captured signals Conceive, write, and submit proposals to develop and expand a research program investigating signal collection and analysis for mission objectives Qualifications: A PhD
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optimization, and application-driven performance analysis for HPC, scientific Artificial Intelligence (AI), and scientific edge computing. We are a leader in computational and computer science, with signature
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experience in hydrological or Earth system modeling, with emphasis on process understanding and prediction. Strong background in computational sciences, including numerical methods, high-performance computing
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, and optimize preprocessing pipelines using HPC resources, targeting scalable execution and automation. Collaborate with domain scientists to integrate pipelines into end-to-end AI workflows specific
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Experience with numerical computing using programming languages such as C++, Python, etc. Author or co-author of open literature publications Special Requirements: Applicants cannot have received their Ph.D
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, with the goal of demonstrating a path towards fault-tolereant quantum advantage in simulating complex material systems. The position will involve a combination of algorithmic design, numerical
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uncertainty quantification. The position comes with a travel allowance and access to advanced computing resources. The MMD group is responsible for the design and development of numerical algorithms and
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, classification, and interpolation of pixel detector data. Exploration of spike-based data encoding/decoding strategies. Hyperparameter optimization using advanced computing resources (e.g., HPC clusters). Detector