Sort by
Refine Your Search
-
sequencing, Hi-C, and other protocols bioinformatic and statistical analysis of complex datasets that include numerous types of data including 16S, metagenomic, metatranscriptomic, and enriched metagenomic
-
diseases, including cancer • Conduct cellular and molecular biology experiments • Produce and purify AAVs (adeno-associated viruses) • Conduct bioinformatic analysis of data 20% Professional Development
-
Informatics (IHI), University of Minnesota, Twin Cities. Dr. Bayat’s team develops highly scalable and computationally accelerated medical imaging and analysis methods to assist in enhanced diagnosis and
-
applications from diverse candidates and are committed to creating an inclusive and supportive research environment. Job Responsibilities Data Analysis and Publication (50%) Test hypothesis around developmental
-
applications from diverse candidates and are committed to creating an inclusive and supportive research environment. Job Responsibilities Data Analysis and Publication (50%) Test hypothesis around developmental
-
approaches. • Drive a project from the conceptual stage to publication. • Identify funding opportunities and apply for grant funding. Data Analysis & Scientific Communication (15%): • Maintain a detailed and
-
experimentation, data analysis, and scholarly communication. Experience with plasma chemistry, catalytic lignin upgrading, nanomaterial synthesis, biobased materials, and biochar characterization will be highly
-
/pharmacodynamic data analysis in the presence of high-dimensional covariates for the improved model-informed decision making. The initial duration of this position is 1 year, but may be extended or a second and/or
-
development, and disseminate results at conferences. This position will work Monday-Friday with weekends as needed. Expected distribution of duties includes: ● 75%: Laboratory benchwork ● 25%: Data analysis
-
analysis of data including measures of pupil dilation, microsaccades, and behavioral measures of speech perception. Experience with data collection and statistical modeling of time-series data are essential