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Field
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emerging to address the ‘broken system’ of antibiotic R&D. It focuses on the actors and stakeholders seeking to develop a radically altered antimicrobial innovation ecosystem by establishing alternative
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expertise in respiratory physiology and pertinent cellular and/or molecular mechanisms. Technical expertise in computer programming languages including R, Phython, and LabView are welcomed. Demonstrated
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). Knowledge of environmental sustainability, soil health, or plant-microbe interactions. Proficiency in the use of bioinformatics tools for metagenomic and transcriptomic data analysis (e.g., QIIME, DADA2, R
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publications in peer-reviewed journals, demonstrating a commitment to scientific excellence and innovation. Experience with data analysis pipelines, programming (e.g., Python, R), and bioinformatics software
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
to program fluently in at least one common scientific programming language such as Python, R, Javascript, or Matlab. Must have experience in sediment transport modeling. Preferred Qualifications, Competencies
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, Room 115A, Bloomington, IN 47405-4801. Questions regarding the position may be directed to Eric R. Walsh-Buhi, erwals@iu.edu . Additional Qualifications Preferred Qualifications: Strong qualitative and
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coding environments (e.g., R, Python). Ability to work collaboratively with a team of diverse backgrounds. Excellent written and verbal communication skills. Experience in processing large data sets
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conferences. It is essential that you hold a PhD/DPhil in computational biology, genomics, bioinformatics, computer science, statistics, or a related field together with strong programming skills in Python, R
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learn new advanced analysis techniques (e.g., in Matlab, R, or Python) if relevant for the task. Write up research results in the form of journal articles. Participate in and co-arrange national and
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detectors at Hanford, Washington and Livingston, Louisiana, which have made the first confirmed detection of gravitational waves. A vigorous LIGO Laboratory R&D program supports the development