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with the application of Algorithms, Artificial intelligence (AI), and Machine Learning (ML) methods to accelerate material discovery and design, optimizing manufacturing processes in nanoscience
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National Aeronautics and Space Administration (NASA) | Hampton, Virginia | United States | 5 days ago
questions in Earth System science is also a goal of this opportunity. Efforts are expected to be conducted in collaboration with the SAGE algorithm/data processing and validation teams, as
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models, report formats and other analysis considerations, determine and write statistical considerations and algorithms for protocol documents according to study design and appropriate statistical methods
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opportunity to develop cutting-edge AI-enhanced algorithms for analyzing transposable elements (TEs) in cancer epigenomics, with direct translational applications to precision oncology and immunotherapy
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electronic health data for application of machine learning or artificial intelligence tools, interoperability with EHR systems, and evaluation of algorithm predictive performance. The Assistant Professor is
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systems. This work will specifically focus on combining ML algorithms with classical data analysis and control techniques to develop robust in situ (i.e., in real-time, during the operating experiment
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complex analysis and utilizes advanced algorithms and statistical software. Adheres to all protocols. Essential Functions The ideal candidate will have demonstrable experience in managing unstructured and
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and utilizes advanced algorithms and statistical software. Adheres to all protocols. Essential Functions Working with PC related hardware equipment, software applications and telephony video
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machine learning algorithm to interpret function machine learning variants. Perform broad lab duties including ordering general lab supplies and maintain budget sheet. Perform other duties as assigned
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bioinformatics analysis pipelines for processing RNA-seq, single-cell RNA-seq, genomics and proteomics data. Develop novel algorithms and integrated data visualization applications when existing software packages