57 modelling-and-simulation-of-combustion-postdoc Postdoctoral positions at The Ohio State University
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experiments in protein engineering, molecular biology, biochemistry, and next-generation sequencing (NGS). The ideal candidate will have experience with computational tools for protein modeling and design—such
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, Biomedical/Health Informatics or Computer Science. Strong quantitative background in pharmacoepidemiologic methods, bioinformatics, causal inference modeling, AI/ML methods. Prior experience with analyzing
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transgenerational plasticity shapes individual responses to both natural and human-induced environmental change, using fish as model organisms. The successful candidate will have flexibility in determining
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blots, confocal microscopy, cell culture, traditional and quantitative real-time PCR, immunoprecipitation, microdissection and/or biomechanical testing and modeling. Experience working with animal models
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. Experience with transportation or housing-related research, including familiarity with transit-induced displacement literature. Familiarity with spatial econometrics and discrete choice modeling. Experience
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identifying and conducting interviews with pesticide applicators, coding responses to interviews and integrating interview responses using a mental models approach. It is expected that the successful candidate
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development; analyzes changes in gene copy number and mRNA or protein expression, gene cloning and mutation detection; participates in analyzing data for reports for the purpose of grants submissions; trains
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| Materials Science and Engineering Position Description: Perform research in light metals and manufacturing including both experimental and modeling work; produces publications and prepares presentations
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mutation detection; participates in analyzing data for reports for the purpose of grants submissions; designs and conducts pre-clinical studies using a variety of disease models in mice; trains staff
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Services Research, Statistics/Biostatistics, Biomedical/Health Informatics or Computer Science. Strong quantitative background in pharmacoepidemiologic methods, bioinformatics, causal inference modeling, AI