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Field
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Profile: A Master`s degree and an excellent PhD degree in Biochemistry, Chemistry, or a related Molecular Science Proven Track Record in Machine Learning, Molecular Simulations, Chemoinformatics
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microbiology, bacteriology (BSL2), molecular biology, cell culture, microscopy, and statistical analysis, and expertise in either infectious disease research. We are looking for someone with an interest in basic
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genomics, metabolomics, or microbiome analysis Computer science, particularly machine learning, artificial intelligence, data science, or computational biology Mathematics or statistics, with experience in
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accepted online at: | https://unmc.peopleadmin.com/postings/87589 Individuals from diverse backgrounds are encouraged to apply. Required Qualifications • A PhD by time of hiring in a relevant field. Relevant
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, and other media Required Qualifications Educational Requirements PhD degree in a relevant field (environmental health sciences, environmental engineering, microbiology, genomics, biochemistry, or other
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Demonstrated ability to conduct independent research and publish in peer-reviewed journals. Proficiency in data analysis and statistical methods relevant to packaging research. Excellent technical writing and
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for quality control, supervision of data entry/data analysis, analysis of research hypothesis using descriptive and multivariate statistics, and the development of independent and collaborative presentations
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programs for statistical and process-based models, writing journal articles and research proposals, working collaboratively with faculty and graduate students, and mentoring graduate student research
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-of-the-art data management, machine learning and statistics techniques. With the advancement of Exascale systems and the variety of novel AI hardware designed to accelerate both training and inference
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working on this and related projects. Qualifications Basic qualifications The applicant applying for the Postdoctoral Scholar must have a PhD degree in Mechanical Engineering. Excellent written and verbal