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that combines modern machine learning approaches with large-scale biological data to automate genome curation by detecting, interpreting, and correcting structural errors, reducing manual effort from weeks
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approaches to characterize microbial community structure and function, working with graduate students, manuscript preparation and the potential to follow up on observations in research models depending
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to characterize microbial community structure and function, working with graduate students, manuscript preparation and the potential to follow up on observations in research models depending on the interest
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associate to develop deep learning algorithms: 1) to model 3D protein complex structures and impact of mutations/PTMs on protein structure and interactions; and 2) to dissect functional elements (e.g
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health and well-being, cognitive aging and dementia, loneliness and social isolation, and integrative data analysis. Strong analytic skills such as structural equation modeling, multilevel modeling
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the appointment start date; demonstrate strong expertise in computational biology or data-driven modeling, with experience in one or more of the following areas: machine learning or deep learning, structural
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. Strong analytic skills such as structural equation modeling, multilevel modeling, longitudinal data analysis, and/or categorical analysis (e.g., growth mixture modeling) using R, Mplus, and/or SAS
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our team as a Postdoctoral Associate in Engineering Education Research. The REDES team works on projects that examine and transform the interconnections, structures, and transition points
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motivated Postdoctoral Associate to lead, develop and support innovative research at the intersection of microbial biotechnology, space biology, and sustainable solutions for plastic and electronic waste
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biotechnology, space biology, and sustainable solutions for plastic and electronic waste recycling. The successful candidate will join a growing space biotechnology team working to understand how microorganisms