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advanced AI/ML methods for robust analysis and integration. Data sparsity, batch effects, and missing values across different omics layers and platforms. Cross-omics data fusion and representation learning
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d) excellent written, oral communication skills e) strong data analysis skills. Ideal applicants will also have experience with some combination of: a) Machine learning e) code optimization and
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need you to have a high aptitude and passion for learning how to use new technology, and working productively with others who may have different skillsets and knowledge. You will need to be comfortable
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completion) in AI, Machine Learning, Data Science, Control or Energy Systems Engineering, or a related field. Strong expertise in AI for real-time systems, predictive analytics, or Digital Twins. Experience
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&M AgriLife is uniquely positioned to improve lives, environments and the Texas economy through education, research, extension and service. Click here to learn more about how you can be a part of
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&M AgriLife is uniquely positioned to improve lives, environments and the Texas economy through education, research, extension and service. Click here to learn more about how you can be a part of
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on methods such as functional connectivity analysis, brain network analysis, or machine learning; Excellent scientific writing and communication skills in English; Ability to work independently while
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records from satellite data, and/or improved methods of uncertainty characterisation, including the use of artificial intelligence and machine learning to improve or analyse satellite climate data records
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in combination with other machine learning techniques, to create predictive models. You will engage in an interactive feedback loop with domain experts to analyze discovered models and remove any
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skills and experience and interest in data analysis, data science, machine learning and process automation would be an advantage. Previous experience with XAS or other synchrotron-based techniques would be