19 parallel-processing-bioinformatics Postdoctoral positions at Medical College of Wisconsin
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platform enables us to test hundreds of different conditions in parallel and assess their impacts on human immune responses, such as antibody production. We routinely work with industry partners to exploit
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platform enables us to test hundreds of different conditions in parallel and assess their impacts on human immune responses, such as antibody production. We routinely work with industry partners to exploit
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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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the harnessing and optimizing of T cell function for cancer immunotherapy using genetically modified mouse models, flow cytometry, q-PCR, RNA-seq, western blot, single cell RNA seq, bioinformatics, and
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), interpersonal, and organizational skills. Proficiency with computer aided design and computational modeling software packages (e.g.; SolidWorks, Ansys, Abaqus, Fluent, SimVascular, etc). Preferred Schedule: Full
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working with CRISPR editing tools is essential, and working with 3D cell line models is preferred. Experience with processing and analyzing genomic sequencing data is essential, and working with
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eventually treat visceral pain disorders. Interested applicants should apply online and attach their curriculum vitae, statement of research interests, and contact information of three references. If you have
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concepts; mathematics; written and computer documentation; data utilization, problem solving, critical thinking, and writing skills. Skills and abilities: Basic biochemistry techniques including but not
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sequencing, analysis of proteins and enzymes, histological analysis including immunohistochemical techniques. Technical expertise in computer data bases and statistical analyses. Demonstrated proficiency in
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diseases including coarctation of the aorta. This work will involve processing of medical image data, creation of idealized and subject-specific computational models, and/or implementation of a computational