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characterize the role of nuclear pore complex machinery in mediating HIV-1 nuclear entry and subsequent downstream process that leads to productive viral gene integration. The goal of this position is to work
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investigating gene-environment interactions, chemical susceptibility, and effects of exposure on evolutionary processes with a focus on emerging contaminants such as PFAS. Research integrates Caenorhabditis
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processing, or simulation (Python, MATLAB) Experience mentoring junior researchers Salary and Rank Special Instructions Applications received by October 1, 2026 will receive full consideration. However, we
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the processes that take place in the bacterial cell envelope with emphasis into oxidative protein folding. The overarching goal for this position is to make timely progress on our NIH and CFF grants (https
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dietetics training Department Contact for Questions Questions regarding the application process may be directed to [email protected] . Questions regarding the position may be directed to Dr. Ines Gonzalez
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reviewed upon receipt. Best consideration date: 7/21/2026. Expected start date is 10/1/26. Questions regarding the position or application process can be directed to: Prof. Lewis, Department of Chemistry
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interactions. The facilities include full-service histology, microscopy (fluorescent, confocal, and electron), tissue culture, animal surgery and imaging rooms, providing a rich scientific environment for basic
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interactions. The facilities include full-service histology, microscopy (fluorescent, confocal, and electron), tissue culture, animal surgery and imaging rooms, providing a rich scientific environment for basic
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the position or application process can be directed to Prof. Chen-Ting Liao (Liao3[at]IU.edu) Basic Qualifications: • Eligibility according to the project sponsor: (1) U.S. citizenship, or (2) U.S. Permanent
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by Dr. Tim Pleskac (cognitive and decision modeling) and Dr. David Crandall (computer vision and AI). The postdoc will lead the development, integration, and testing of computational models of decision