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Field
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applicants interested in developing a research program in the field of cancer biology are welcomed to apply. Expertise in the fields of molecular biology, cell biology, and genetics are expected. Experienced
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. Collaborative work and teaching within the research team (10%) Qualifications Required Qualifications: Education: - Doctoral degree in bioinformatics, biostatistics, computational (micro)biology, genomics
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more than two dozen programs. Our physician assistant program was recently ranked ninth in the nation by U.S. News & World Report, and our primary care program was ranked 17. The university’s physical
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regenerative medicine. Duties The field of synthetic biology is highly interdisciplinary, combining advanced molecular tools (e.g., CRISPR-based genome engineering), computational algorithms, and DNA/RNA
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. Computational and bioinformatic skills. Experience in microscopy. Generation and analysis of mouse models. Handling of human samples. Molecular biology skills including CRISPR, cloning and qPCR. In vitro cell
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an outstanding doctoral degree in disciplines such as physics, chemistry, mechanical or electrical engineering, biotechnology or equivalent fields and a proven record of high-level research, for example through
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Research Facility (MRRF) at the University of Iowa in collaboration with the Free Radical and Radiation Biology Program is seeking a highly qualified motivated individual to fill a Post-Doctoral Fellowship
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, please reach out to Ambro van Hoof at vanhoof.3@osu.edu . Required Education and Experience: A doctorate degree in the molecular life sciences in genetics, molecular biology, biochemistry, microbiology
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as mathematics, economics, finance, ecology, biology or physics. The ideal candidate has a strong background in mathematical modeling and computational techniques, and an interest in interdisciplinary
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to uncover underlying biological principles Selection Criteria Ph.D. in data science, computational biology, systems biology, bioinformatics, neuroscience, or other related fields Strong experience in data