72 parallel-processing-bioinformatics-"Multiple" Postdoctoral positions at University of Minnesota
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Previous Job Job Title Post-Doctoral Associate - Department of Surgery Next Job Apply for Job Job ID 373041 Location Twin Cities Job Family Academic Full/Part Time Full-Time Regular/Temporary
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or publications. Qualifications All required qualifications must be documented on application materials. Required Qualifications PhD in biological science and/or bioinformatics or computational biology. Knowledge
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species where reference resources remain incomplete. ● Pathology and imaging integration: Develop computer vision approaches for histopathology and radiology, linking image-derived features with genomic and
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in molecular biology, cellular biology, AI-based bioinformatics, and mouse models required, which includes single-cell RNA sequencing and data analysis, hydrodynamic injection, hepatocyte isolation
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surveillance and preparedness planning using multiple modeling approaches. The successful candidate will develop and implement statistical and machine-learning models, integrate multi-source ecological datasets
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, processing and analyses of data acquired as part of multiple team-based research projects, with a primary focus on experiments for Project 2 of the Udall Center of Excellence in Parkinson’s Disease Research
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computing (HPC) and parallel processing to enable the analysis of massive datasets. Experience in advanced statistical inference (e.g., Bayesian statistics, spectral methods) for extracting robust patterns
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other immune parameters in plasma and other sample types. • Perform in vitro viral phenotyping assays • Maintain multiple copies and records of all data collected • Assist in the organization and curation
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initiative Preferred Qualifications: Published microscopy (widefield or confocal) techniques Evidence of prior bioinformatics analysis Published HIV-1 research Literature fluency particularly viral RNA biology
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of GVHD and immunodeficiencies following bone marrow transplantation. This project will involve critical analysis and modification of T-cell and regulatory T-cell development through multiple strategies