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The University of Texas Southwestern Medical Center (UT Southwestern Medical Center) | Dallas, Texas | United States | about 8 hours ago
, protein, genome, and chemical engineers to develop effective and safe immunotherapies for cancer, autoimmune disease, and other conditions. The Center is specifically focused on translating promising
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in the area of the lab. The focus of the Lab is in the area of differential protein expression in the human vascular endothelium, associated with normal or diseased tissues, offers the potential
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of proteins that transfer electrons (i.e., oxidoreductases). It is expected that the Postdoctoral Associate will have expertise in several of the following areas including bioinformatics, bioinorganic chemistry
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) enzyme biochemistry and mechanism. Under the direction of faculty leadership, this position will perform laboratory research using protein overexpression, anaerobic protein purification techniques
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) enzyme biochemistry and mechanism. This position will utilize protein overexpression, anaerobic protein purification techniques, and a variety of bioanalytical, spectroscopic, and structural approaches
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health. Basic science discoveries made using a variety of human and pathogen-derived proteins, designed, expressed and purified by a collaborative DHVI team have contributed to the identification
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(organelles such as chloroplast and protein complexes) in their cellular environment, cryo-electron tomography (cryo-ET) is becoming a pivotal imaging approach. Therefore, CEA Irig is recruiting a researcher to
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regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
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Albert Einstein College of Medicine (Bronx, NY) | New York City, New York | United States | about 2 months ago
to protein expression, purification, and functional characterization, as well as target validation and pathway analysis. Applicants should have a Ph.D. in chemical biology, cell biology, molecular biology
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regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https