Sort by
Refine Your Search
-
Previous Job Job Title Post-Doctoral Associate Biostastics/Statistics Next Job Apply for Job Job ID 365061 Location Twin Cities Job Family Academic Full/Part Time Full-Time Regular/Temporary Regular
-
methods of data analytics (e.g., statistics, stochastic analysis, Bayesian statistical analysis), physically-based hydrology and water quality models, and the use of machine learning tools for modeling flow
-
classes in the graduate and undergraduate curricula and/or similar classes, either in an in-person or online modality: ● Quantitative and Psychometric Methods ● Multivariate Statistics ● Measurement
-
statistical methods to agronomic research, including mixed models, geospatial statistics, multivariate analysis, and machine learning - Must possess and maintain an active and valid driver’s license Preferred
-
Preferred Qualifications: • Demonstrated productivity through first-author and collaborative publications in immunology • Strong background in experimental design, statistical data analysis, and data
-
internet connection for duties undertaken remotely. Qualifications Required Qualifications: A PhD degree in Biostatistics, Statistics, Computer Science or a related field who possess STRONG computing
-
publications in immunology • Strong background in experimental design, statistical data analysis, and data visualization • Prior mentoring experience and capacity for collaborative research across disciplines
-
a laboratory notebook; perform statistical analyses of data obtained from experiments and render interpretations of the data. Operations - 20% • Keep the laboratory stocked, maintain inventories
-
organizational, quantitative analysis and writing skills are necessary. Candidates with a strong background in molecular virology, next-generation sequencing, Bayesian analysis, phylogenetic analysis, statistical
-
: Experience in one or more of the following: * Field research experience * Lab / analytical research experience * Statistical methods * Quantitative and programming skills