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to achieve scalability in terms of the simulator systems. The work will be done in close collaboration with the physics team to be able to develop optimizations also at the algorithmic level in a co-design way
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Computing Applications group in CSD has an immediate opening for a Postdoctoral Research Associate to design, develop, and deploy machine-learning and high-performance computing workflows, algorithms, and
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Polytechnique de Paris, is one of France's top 5 general engineering schools. The mainspring of Télécom Paris is to train, imagine and undertake to design digital models, technologies and solutions for a society
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Post Doctoral Fellowship: Development of a 'Battery Management System' for Lithium-Ion Batteries (11834) About UM6P : Mohammed VI Polytechnic University is an institution dedicated to research and
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will be focused primarily on the development and application of novel computational algorithms to analyze and integrate diverse omics datasets, including single-cell RNA-seq, spatial transcriptomics and
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 2 months ago
include (but are not limited to): Develop algorithms to characterize aerosol speciation from LIDAR fluorescence signals Develop machine learning emulators to represent forward operators for polarimeter-only
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maritime transport, maritime decarbonisation and digitalisation, methodology development and applications Publish findings in top peer-reviewed journals and conference proceedings Collaborate with other
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Computer Vision algorithms. Experience using urban building stock modelling and urban digital twins What you will do: Design & Develop: Create data structures for detailed, spatialised construction component
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heterogeneous multi-omics datasets. Integrative Data Analysis: Perform and lead analysis of large-scale multi-omics datasets, including RNA/DNA sequencing, methylation, and metabolomics. Method Development
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-scale scientific data. Publishing research in leading peer-reviewed journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources