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. News. • Experience querying databases and using statistical computer languages: R, Python, SQL, etc. • Experience visualizing/presenting data for stakeholders using Power BI, Tableau, R, etc. • Practical
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, atmospheric science, computer science, or a related quantitative field. Certification and Licensing: Prior experience working with atmospheric aerosol data and/or machine learning tools in Python or MATLAB is
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using R, Python, and GitHub. The role also involves contributing to data visualization, interpretation, and manuscript preparation; assisting with wet-lab activities such as library preparation, histology
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analysis, basic scripting in R or Python, and integration of multi-omic datasets is considered an advantage. Candidates should also possess a strong publication record in high-impact journals and a
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Information Systems, Computer Science, Bioinformatics, or a related field (as held by candidate). Experience: Experience developing and maintaining data pipelines and ETL workflows using tools such as Python
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score derivation and validation, and other relevant analyses. Develops R or Python scripts for data analysis, statistical modeling, and machine learning techniques, ensuring reproducibility and efficiency
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such as glaucoma, macular degeneration, and uveitis. Programming in Python and R languages with knowledge of Google Tensorflow, PyTorch, scikit-learn, and Keras or other related deep learning libraries
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of major eye diseases such as glaucoma, macular degeneration, and uveitis. Programming in Python and R languages with knowledge of Google Tensorflow, PyTorch, scikit-learn, and Keras or other related deep
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such as glaucoma, macular degeneration, and uveitis. Programming in Python and R languages with knowledge of Google Tensorflow, PyTorch, scikit-learn, and Keras or other related deep learning libraries
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to optimize data processing workflows, particularly for large-volume, high-dimensional healthcare datasets. Utilizes object-oriented programming (e.g., Python, Java) to develop modular, scalable research