The McDonald Lab of Integrative Omics aims to apply state-of-the-art multiomics tools to develop and understand molecular connections underlying human pathologies related to muscle wasting and organ dysfunction in chronic disease. The desired candidate will be prepared to design statistical experiments to support ongoing human subjects research, both prospective and retrospective (i.e., consortium/ cohort-based), as well as to interpret and communicate findings clearly.

The Biostatistics Associate is an intermediate role that independently conducts standard statistical analyses, assists with the preparation of statistical sections of study protocols, and collaborates with researchers to interpret and present data findings. With increased responsibility, the associate ensures data accuracy, contributes to the design and implementation of studies, and begins developing specialized expertise in biostatistical methods. This role plays a significant role in drafting reports, preparing manuscripts for publication, and may start to oversee the work of biostatistics assistants.

Duties and Responsibilities:

• Performs analysis related to ongoing clinical studies
• Collaborates with bioinformaticians to carry out rigorous data practices
• Archives and organizes participant data
• Schedules and oversees participation in research studies
• Interfaces directly with and provides support to study participants
• Performs data quality control and quality assurance methods
• Applies developed statistical tools to internally generated and consortium-based data sets
• Writes documented and validated statistical programs for analysis and reporting
• Creates summaries and presents results in written and verbal form
• Perform other duties as assigned

Salary Range: $55,180 - $71,735

Master's degree in a related field and two (2) years of related experience OR Bachelor's degree in a related field and four (4) years of related experience required. Work experience may NOT substitute for education requirement.

Preferred:

• Proficiency with R and at least one additional coding language (e.g., Linux, Python)
• Comfort with data management, quality control, and standard practices
• Proficiency with applying standard statistical tests and interpreting results
• Ability to handle responsibilities related to multiple ongoing projects at various points in their lifecycle
• Interpersonal skills
  

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