The Department of Medicine is responsible for fulfilling the teaching, research, and clinical missions of the University of California, San Diego and employs 486+ full-time salaried faculty members and 100+ academic appointees. Staff personnel include 600+ staff in 9 bargaining units, students, and volunteers. There are 250 clinical faculty practicing at multiple sites and hospitals.

The Division of Infectious Diseases and Global Public Health (ID+GPH) within the Department of Medicine at UC San Diego aims to eliminate the burdens of infectious diseases and health disparities by delivering outstanding patient care, conducting world-class multidisciplinary health research, directing the institutional response to antimicrobial resistance, preventable healthcare associated infections, and emerging pathogens, and offering leadership, consultation and training on global public health, gender equity, microbiology, and infectious diseases topics.

Under general supervision and with minimal instruction, incumbent will provide statistical, bioinformatics, and data-management support for a multiple-investigator human immunodeficiency virus (HIV)-clinical and -translational research program. Incumbent is responsible for application of a broad range of statistical data analysis methods, including generalized linear and additive models, mixed effects models and other multivariate methods, network analysis techniques, Bayesian methods, power and sample size calculation, statistical methods for genomics and sequence analysis.

Conducts complex statistical analyses, including Bayesian inference, network science, multivariate regression modeling. Builds prediction models using machine learning / AI methods to investigate infectious disease/HIV dynamics. Develops statistical analysis plans for infectious disease/HIV studies. Performs sample size and power analyses to inform study design. Communications statistical results and interpretation for presentations, grant proposals, and academic manuscripts. Uses version control software (e.g., git) to ensure reproducibility of analyses. Reviews, cleans, and prepares data for analysis. Keeps informed of statistical, machine learning, and AIadvances.

Uses skills as a seasoned, experienced research professional with a full understanding of in-depth statistical analyses and / or research software programming techniques in study design; data analysis; and protocol, grant, and manuscript preparation. Demonstrates good judgment in selecting methods and techniques for obtaining solutions.

• Seven years of related experience, education/training, OR an Bachelor's degree in related area plus three years of related experience/training.

• Thorough knowledge of research function. Graduation from college with a major in statistics or a related field and three (3) years of professional statistical experience; or an equivalent combination of education and experience; andknowledge and abilities essential to the successful performance of the duties assigned to the position. Master'sdegree is preferred.

• Thorough skills associated with statistical analysis and systems programming. Demonstrated working experience with statistical methods and models incorporating a broad range of study designs and traditional and modern statistical approaches such as linear, logistic, Poisson, survival and longitudinal models, multiple testing adjustment methods,Bayesian inference, network science, multivariate regression modeling and machine learning techniques.

• Thorough skills in analysis and consultation.

• Skills to communicate complex information in a clear and concise manner both verbally and in writing. Experience providing written interpretation of statistical methods and results, in a manner suitable for publication. Experiencepresenting finding and progress of project to study staff throughout the project. Excellent time management skills.

• Skills in project management. Demonstrated skill in prioritizing multiple responsibilities and tasks. Excellent organizational skills.

• Research skills at a level to evaluate alternate solutions and develop recommendations.

• Demonstrated experience with statistical programming and use of statistical computer packages, including SAS and R.

• Demonstrated ability to read complex scientific literature, understand appropriate study design, formulate appropriate statistical hypotheses, and propose appropriate statistical methods.

• Demonstrated knowledge of Word, Excel, Power Point, and relational database concepts.

• Demonstrated skill in prioritizing multiple responsibilities and tasks. Excellent organizational skills.

• Demonstrated use of version control software (e.g., git) to ensure reproducibility of analyses.

• Experience with clinical trial protocols.

• MS or PhD in statistics preferred.

• Employment is subject to a criminal background check.