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Field
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measurements Calibration of materials as sensors to measure temperature, oxygen, and pH values in cells Development of models based on artificial intelligence algorithms to interpret luminescence signals Study
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candidates which are explored in more depth. In particular you will work on the extension, development and analysis of new quantum algorithms for near-term and fault tolerant quantum computers for drug
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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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Are you excited about pioneering experimental quantum computing? Do you want to be part of a world-class research environment developing the next generation of superconducting quantum processors? We
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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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details below, as well as a short presentation of the project. TFor the longest time, the very definition of social media revolved around the concept of user-generated content. However, recent developments
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of codes and algorithms. We will focus on devising computational solutions that can immediately be of use in other applications contexts as well. The candidate’s work will entail the development and
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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
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journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration and validation
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by integrating large-scale single-cell foundation models with structured biological knowledge encoded in genomic graphs. The project will also deliver efficient algorithms to train these models under