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for radiopharmaceutical and particle therapy research with GMP-grade therapeutic product development facilities. Extensive shared resources for genomics, proteomics, metabolomics, imaging, and computational biology. A rich
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doctoral degree in applied mathematics, physics, computer science, biomedical engineering, mathematical biology, computational systems biology, or related field. Demonstrated experience in at least one of
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imaging program involving molecular oncologists, cancer biologists, computational biologists, and imaging scientists focused on detecting breast cancer and predicting response to therapy. The position is
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genetics and genomics, with expanded interests in computational biology, functional genomics, and neuroscience. Example projects within the university and with external partners: • Noncoding Variation in
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collaboration with Dan Eisenberg, Associate Professor of Anthropology. Ideal applicants will have broad interests in the evolutionary biology of living humans and/or non-human primates. Job duties will be adapted
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cytoskeleton and membrane trafficking. • Utilize quantitative, biophysical, and computational approaches to cell biology, including fluorescence imaging, image analysis, and biophysical modeling. • Experiment
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Position Summary The Foltz lab works at the intersection of translational immunology and computational biology. We study mechanisms of response and resistance to natural killer (NK) cell therapies
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, Bioinformatics, Molecular Biology, Developmental Biology, Computational Biology, etc.). Exceptional skills in molecular biology, genomics, human cell culture, and bioinformatics. Preferred Qualifications Education
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the Required Qualifications section. Work Experience: No additional work experience beyond what is stated in the Required Qualifications section. Skills: Collaboration, Computational Biology, Data Analysis, Data
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, Fisheries Science, Biology, Zoology, Biological Oceanography, Mathematics, Statistics, Computer Science, or related discipline Knowledge of modeling ecosystem and/or social network dynamics Strong