| Company Information:
Division of Biomedical Modeling and Informatics, Dept of Biostatistics & Computational Biology
Position Title:
Research Assistant MS Statistician
Duties & Responsibilities:
Under general direction and with latitude for independent judgment and initiative, Research Assistant will serve as a critical resource for the Division of Biomedical Modeling and Informatics (Dr. Hulin Wu, Director), providing direct biostatistical support, statistical programming, and data management for research studies of the newly funded UR Respiratory Pathogens Research Center (RPRC). Candidate will work with a team of statisticians, bioinformaticians, and database developers to support the RPRC in the conduct of translational and clinical research studies on immune responses to influenza, RSV and other viral pathogens. RPRC studies include 1) evaluation of factors that determine clinical severity of RSV infection response, 2) assessment of the impact of respiratory virus infections on the respiratory function in infants, 3) determination of the immune correlates of protection from influenza in human vaccine challenge studies, 4) and other immunogenicity studies in mice and humans. The candidate will also perform similar analyses, supporting senior statisticians in other related immunology and virology research projects/analyses as directed by the Dr. Wu. Specific job responsibilities include: (1) The candidate with minimal guidance will perform data analysis, such as univariate descriptive statistics, fitting generalized linear and mixed effects models, check model assumptions, create summary tables and plots. (2) The candidate will provide support to study investigators in the development of study designs, evaluation of study endpoints for appropriate statistical methods, and calculation and justification for study sample size. (3) The candidate will prepare study analysis plans, perform periodic reporting as warranted by the study guidelines. Create specialized reports related to studies based on parameters provided by study researchers as warranted. (4) The candidate will clearly present statistical methods, results, and conclusions to study teams of multi-disciplinary investigators. (5) The candidate will provide statistical programming in SAS or R, working with large databases of different formats to combine and transform them into analysis datasets and will maintain codebooks and documentation of all dataset activities. (6) Plan, implement, coordinate, operate, and evaluate a study protocol for retrieving and storing data, working closely with database Bio-Lab Informatics Server (BLIS) team members and with collaborators at the RPRC. (7) Develop and implement standardized quality and logic checks to validate data accuracy. Work with research clinic and labs to correct data errors and maintain documentation in database for easy referencing to ensure consistency in the decision making process. (8) Develop and test data management tools using the web-based data management system, BLIS, by providing analysis guidance and acting as liaison between BLIS database developers and lab investigators.
Position Qualifications:
Master’s degree in a related discipline such as, Statistics, Biostatistics, Epidemiology, Public Health, Mathematics, Science or Engineering, with 3-5 years of related experience managing, merging, and analyzing large databases, or equivalent with combination of education and experience. Proficiency in statistical analyses and a strong background in SAS or R statistical programming required. Experience with MS Excel, and other statistical programming packages preferred. Background in immunology/biology or experience in laboratory bench work desirable. Excellent written and verbal communication skills and ability to interact with an interdisciplinary team of investigators and staff of all levels in a professional manner is required.
Salary Range:
Benefits:
Web Site:
http://www.urmc.rochester.edu/biostat/
Application Address:
www.rochester.edu/working/hr/jobs Job Code 174339.
Contact Email:
Application Deadline:
MM/DD/YYYY
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