Location: Gainesville, FL
Cap-Exempt H-1B Position — No lottery required
**JOB NO:** 540511 **WORK TYPE:** Post Doc Associate **LOCATION:** Main Campus (Gainesville, FL) **CATEGORIES:** Biology/Life Science, Business/Accounting/Finance, Agricultural Sciences **DEPARTMENT:** 60220000 - AG-STATISTICS **CLASSIFICATION TITLE:** Postdoc Aso **CLASSIFICATION MINIMUM REQUIREMENTS:** The appointee shall have received the doctorate in a field appropriate to the assigned duties and responsibilities. **JOB DESCRIPTION:** The Institute of Food and Agricultural Sciences is creating an environment that affirms community across all dimensions. If an accommodation due to a disability is needed to apply for this position, please call 352-392-2477 or the Florida Relay System at 800-955-8771 (TDD) or visit Accessibility at UF . This is a postdoctoral associate position (100% Research) available in the Statistical and Data Analytics Consulting Unit, University of Florida – Institute of Food and Agricultural Sciences (UF/IFAS). This assignment may change in accordance with the needs of the unit. Duties will include supporting plant breeding programs at the University of Florida and the USDA-ARS funded Breeding Insight program by identifying and implementing solutions related to experimental design, statistical analysis, data management, and analytical software tools. The position will also include delivering training and supporting students, staff, and faculty. Responsibilities of the position include: - Implementing and running data analysis from plant breeding programs. Ensuring compliance with data security standards and compatibility with R-based and/or Python analysis tools and Shiny apps to maintain open-source and availability to the public. [Approximately 40% effort] - Assisting and maintaining data collection evaluation, curation, storage and analysis methods to improve data security, accuracy, operation, efficiency and summary report generation. [Approximately 20% effort] - Developing and maintaining procedures, handouts for practical data analysis