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handling stations. · Evaluate formulations in cell culture and animal models. · Collaborate with our team to conceive, implement, and test novel computational methods for drug carrier design
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functional data analysis, tensor regression, high-dimensional variable selection, longitudinal and survival analysis, machine/deep learning, bioinformatics methods in -omics data are preferred. Demonstrated
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communities; Familiarity with Mainline Protestant denominations and/or seminary education is highly desired. Experience doing mixed-methods and/or quantitative research; Experience with quantitative data
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the Bartesaghi Lab at Duke University to work in the development of image analysis and machine learning methods applied to protein structure determination using single-particle cryo-electron tomography (ET
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environment at Duke is ideal for our translational research efforts. Applicants must : 1. Hold a PhD with relevant skillsets in programming (including Python) and machine learning methods for image
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utilize new machine learning methods for 3D behavior tracking and analysis. · Advise PhD students on related projects. Other Work Performed and Expectations · Document progress consistently and
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. Ability to execute appropriate computational and statistical analyses and present data in 5. Abililty to learn from existing literature to develop new methods and strategies to analyze complex datesets. 6
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the forefront of epitranscriptomics research and develops cutt ing-edge methods to understand functional roles of RNA methylation in the control of gene expression. We have several exciting projects aimed at new
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conclusions from research results and report/write results of research studies for publication; Review methods manuals, scientific journals, and other literature for information applicable to research and write