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. Analyze large datasets from battery systems to improve model accuracy and performance. Conduct research on predictive analytics for real-time battery health monitoring and fault detection. Collaborate with
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perovskite thin films applications using slot-die coating and other large-area deposition methods. Analyze experimental data to optimize material and device performance, write scientific reports, and publish
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international users in water and food systems. Job Description: Over the past few years, advances in computational power and the increasing availability of large volumes of remote sensing data with finer spatial
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interdisciplinary applied research projects. From technological innovation to the transfer of research to industry, Vanguard has also the mission of developing an ecosystem of related start-ups. For more information
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consulting and data management services to UM6P researchers and their collaborators. UM6P has state of the art NGS sequencers and mass spectrometry and the largest HPC (High Performance Computing) cluster in
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spatial distribution of critical topsoil properties in global drylands. Process large-scale geospatial and remote sensing datasets using High Performance Computing (HPC) systems. Conduct data analysis, and
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a large and diverse range of healthcare needs. Our approach is to provide personalized, practical care for each patient Job Description The candidate will be required to: Prescribe a treatment program
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perovskite thin films applications using slot-die coating and other large-area deposition methods. Analyze experimental data to optimize material and device performance, write scientific reports, and publish
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, large-scale measurements that can be used to estimate surface variables of interest. In particular, radar data can nowadays be used to obtain maps of surface soil moisture at a high spatial resolution (a
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algebra algorithms, including sparse/dense linear systems solving and preconditioners. Scalable implementations of linear algebra methods targeting large-scale HPC systems. Optimization of linear algebra