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performs MRI research and development of advanced multiparametric methods for the evaluation of primary and metastatic brain tumors. Recent work incorporates machine learning methods to advance
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propagation, titration such as plaque assays or TCID50, neutralization assays) Immunological methods (ELISA, Western blotting, flow cytometry, immunofluorescence microscopy) Basic bioinformatics and data
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methods (e.g., SHAPE, DMS mapping, RNase digestion).Experience in protein expression, purification, and RNA–protein complex reconstitution. Exposure to small-molecule screening or RNA-targeted drug
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receptor signaling. Our lab uses a variety of biophysical techniques to characterize protein structure and dynamics in these studies, notably continuous-wave and pulsed EPR methods such as DEER spectroscopy
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biophysical methods of GPCR function. Projects will involve protein expression/purification, cryo-EM structure determination, X-ray crystallography, radiolabeling kinetic studies, and possibly using biophysical
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. Proficiency with computer aided design and computational modeling software packages (e.g.; SolidWorks, Ansys, Abaqus, Fluent, SimVascular, etc). Sufficient knowledge of program study area. Preferred Schedule
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longitudinal modeling, machine learning methods, subgroup analysis, or other advanced modeling techniques is highly desirable. Software Proficiency: Experience with neuroimaging tools such as AFNI, SPM, FSL
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expertise in respiratory physiology and pertinent cellular and/or molecular mechanisms. Technical expertise in computer programming languages including R, Phython, and LabView are welcomed. Demonstrated
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statistical analysis and computer programming in any of the following areas are highly valued: structural equation modeling, mixed effects modeling, mediation analysis, spatial modeling, web-based mapping