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learning, or a related field Strong background in deep learning and statistical analysis Proficiency in Python, R, and deep learning frameworks (e.g. PyTorch, TensorFlow) Strong written and verbal
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, biostatisticians, pathologists, data scientists, molecular biologists, and clinical researchers, all of whom contribute their unique expertise to our lab’s work. We employ a broad variety of analysis approaches and
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interdisciplinary teams, the design and execution of research studies and data analysis, with an overall goal to further the mission of St. Jude to advance research and cures for pediatric catastrophic diseases. St
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data, bias analysis and minimization, performance metrics and uncertainty quantification, evaluation of continuously learning algorithms, and post-market monitoring. Learning Objectives: Under
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. Required competencies: Strong background in bioinformatics (e.g., R, Linux, Python). Experience working with large cohorts and high-dimensional data. Experience with microbiome analysis and/or GWAS
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productivity, along with excellent written and verbal communication skills. Experience with bioinformatics and programming for analysis of sequencing-based datasets (DNA, RNA, epigenetic) is highly valued
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a related field who bring hands-on expertise in in vivo calcium imaging or electrophysiology, along with strong data analysis experience in Python and/or MATLAB. Candidates who combine quantitative
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(http://vanallenlab.dana-farber.org/) to work on the analysis of new datasets generated in the context of multiple clinically oriented cancer sequencing projects in order help advance efforts
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cells, antigen-presenting cells, cell culture, immunological techniques, multicolor flow cytometry, scRNA analysis are highly desirable. Please include the following information with your Resume/CV: Cover
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of sulfide research on Southwest Indian ridge: Major Research in Geophysics, Sulfide mineralization, Resources assessment The big data analysis on geochemistry of seabed igneous rocks and its applications