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Field
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scientific applications * Researching digital and post-digital computer architectures for science * Developing and advancing extreme-scale scientific data management, analysis, and visualization * Developing
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of multiple dataset) with a strong focus on single-cell RNA and ATAC sequencing and spatial transcriptomic data. A demonstrated interest in data visualization and large-scale data analysis is highly
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methods. Develop data visualization products and synthesize findings to support research conclusions. Essential Function Yes Percentage of Time 25 Job Duty Grant Support, Publications, and Scientific
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methods. Develop data visualization products and synthesize findings to support research conclusions. Essential Function Yes Percentage of Time 25 Job Duty Grant Support, Publications, and Scientific
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data analytics through real-world projects that support University operations. Fellows partner with campus stakeholders to understand business needs and translate them into analytics solutions
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collecting data. Statistical skills, including data analysis and visualization. Familiarity with programming, including programming skills in R and/or Python. Preferred Qualifications Experience with or
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, PyTorch, and LLMs; Skilled in data visualization using Matplotlib, Seaborn, and ggplot2, and experienced in managing research projects with tools like Git/GitHub, ClickUp, and Jupyter Notebooks
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computing and data analysis, storage, visualization. The Fellowship honors Dr. Alston S. Householder and recognizes his seminal research contributions to the fields of numerical analysis and
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extensive experience in libraries and frameworks such as Pandas, NumPy, scikit-learn, Gensim, BERTopic, TensorFlow, PyTorch, and LLMs; Skilled in data visualization using Matplotlib, Seaborn, and ggplot2
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interaction of various types of electromagnetic radiation with molecules. Fluorescent molecules are among the most often used visualization modalities. The research group Fluorescent Probes led by Dr. Peter