37 molecular-modeling-or-molecular-dynamic-simulation Postdoctoral positions at Texas A&M University
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molecular biologists to develop and parameterize models of genetic control systems • Calibrating epidemiological models to available mosquito-borne disease data • Contributing to related research on vector
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Letter & Resume: A cover letter and resume are strongly recommended. Required Education Appropriate PhD in a related field Preferred Qualifications One year of research experience in molecular biology and
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system using mouse models. Techniques may include confocal imaging, brain slice electrophysiology, in vivo manipulations, molecular biology, and behavioral analysis. Genetic mouse models will be applied
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Qualifications Experience working with mouse models, viruses, helminth models and immune cells. Experience with molecular biology techniques (e.g., PCR, cloning, sequencing, CRISPR-Cas). Experience with virology
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, pathogenesis, and drug discovery. Expertise in molecular genetics, protein biochemistry and animal models is highly preferred. The ideal candidate will conduct high-quality research using advanced techniques in
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chemical biology and sequencing-based approaches to understand how RNA structure and dynamics regulate protein recognition. The associate will play a key role in advancing the lab’s research program by
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models of neurological and neurodegenerative diseases. Biochemical and molecular biological assays such as ELISA, WB, qPCR and flow cytometry. Immunofluorescence and confocal microscopic techniques
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confocal imaging, brain slice electrophysiology, in vivo manipulations, molecular biology, drug discovery and behavioral analysis. Applies genetic mouse models. Conducts experiments, analysis, preparation
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. Responsibilities include expanding the capabilities of current ocean model applications, with emphasis on hydrodynamics, coastal flooding, biogeochemical simulations, and the dispersion of coastal pollutants and
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for simulating river network dynamics, such as R, Julia, Python, or GIS-based hydrological modeling platforms. Ability to integrate physical, chemical, and biological components into the river-lake network models