Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
, organize, and analyze environmental sampling data; develop data visualizations; conduct exposure pathway analyses; and evaluate the public health implications of potential chemical exposures. You will have
-
institution systems may be submitted. Click here for detailed information about acceptable transcripts. A current resume/CV, including academic history, employment history, relevant experiences, and
-
data visualization tools. Gain experience with metrics and statistical analysis. Learn to employ industry standard techniques to implement IT systems. Gain experience using security compliance
-
modeling pipelines from data extraction and processing through all stages of modeling and visualization of results. Proficient with programming languages commonly used in quantitative ecology (e.g., C
-
integration, intelligent document processing, workflow design, and data visualization techniques associated with HR, Budget, and Travel scenarios. Activities may include examining methods for translating
-
opportunity to develop dashboards and other visualizations to support data-informed decision making. In addition, you will build scientific communication and professional development skills through
-
research priorities. Additionally, you will learn to synthesize complex scientific findings into technical evaluations, author peer-reviewed manuscripts, and develop empirical data visualizations
-
to improve efficiency, product quality, and scalability; Interpret experimental data to support research and operational decision-making; Develop proficiency in the use of data analysis, visualization, and
-
Salmonella microbiology (culture, isolation, characterization) Molecular characterization and genetic typing Whole-genome sequencing Transcriptomics Data analysis Data visualization Point of Contact Sara Beth
-
of the appointment start date. Master's is preferred, however bachelor's degree in data science or related field will also be considered. Preferred skills: Data analysis and visualization Strong analytical and problem