A cover letter is required for consideration for this position and should be attached as the first page of your resume. The cover letter should address your specific interest in the position and outline skills and experience that directly relate to this position.

The University of Michigan Health System improves the health of patients, populations and communities through excellence in education, patient care, community service, research and technology development, and through leadership activities in Michigan, nationally and internationally. Our mission is guided by our Strategic Principles and has three critical components; patient care, education and research that together enhance our contribution to society.

The Chronic Pain and Fatigue Research Center (CPFRC) at the University of Michigan is a pioneering interdisciplinary center dedicated to advancing our understanding of chronic pain and fatigue disorders. Since our founding in 1998, we?ve been leaders in identifying how distinct conditions?such as fibromyalgia, interstitial cystitis, osteoarthritis, low back pain, and post-deployment syndromes often share common biological mechanisms.

What we offer:

A collaborative, intellectually stimulating environment with mentorship from experienced faculty biostatisticians.

Exposure to a rich and diverse research portfolio spanning NIH-funded multi-center trials, longitudinal cohorts, and translational studies.

Strong opportunities for career development, skill growth in advanced statistical methods, and contributions to peer-reviewed publications.

Hybrid work schedule with flexibility; full-time, regular appointment.

Access to the University of Michigan?s world-class research infrastructure, training programs, and academic community. 

Statistical Analysis

Conduct statistical analyses across a range of study designs and data types, following Statistical Analysis Plans (SAPs) developed by the Faculty Statistician, including:

• Longitudinal & repeated-measures studies (e.g., linear/nonlinear mixed-effects models, GEE, repeated-measures ANOVA)

• Survival & time-to-event analyses (e.g., Cox proportional hazards, Kaplan-Meier, competing risks, accelerated failure time models)

• Observational & cross-sectional studies (e.g., logistic regression, ordinal regression, GLMs, propensity score methods)

• Dimension reduction & exploratory analyses (e.g., PCA, factor analysis, latent class analysis)

Perform model diagnostics, sensitivity analyses, and QA checks on all delivered analyses; communicate findings and any analytical concerns proactively to the Faculty Statistician.

Develop and execute well-documented, reproducible analysis code in R and/or SAS, using platforms such as Quarto or R Markdown for reproducible reporting.

Produce publication-quality tables, figures, and data summaries for manuscripts, conference presentations, and sponsor reports; address statistical reviewer comments on manuscripts in collaboration with the Faculty Statistician and investigators.

Data Quality & Management

Collaborate with Data Managers to clean, validate, and transform raw datasets into analysis-ready analytic files aligned with SAP specifications.

Perform data quality checks, evaluate data validity, and document all data preparation steps, input/output file locations, and version histories.

Write programs for data acquisition, preparation, and analytic file creation across multiple concurrent studies (single-center and multi-center).

Manuscript & Grant Support

Contribute to the statistical methods and results sections of research manuscripts; support the peer-review and revision process.

Provide statistical input for grant proposals, including assistance with power and sample size calculations, analysis plan narrative, and analytical approach sections ? under the guidance of the Faculty Statistician.

Participate in research presentations at internal meetings, conferences, and workshops as appropriate.

Collaboration & Communication

Serve as an active member of project teams comprising faculty investigators, data managers, study coordinators, and research trainees; contribute to weekly triage meetings and project stand-ups.

Communicate clearly and proactively with the Faculty Statistician and Principal Investigators about analytical progress, results, and any data or methodological issues.

Uphold CPFRC standards for data governance, documentation, and reproducibility.

• Bachelor's degree with 1-3 years of professional experience
• Previous coding and data analysis experience, including relevant research project experience gained during training.
• Strong theoretical and applied foundation in statistical methods, including linear and nonlinear regression, generalized linear models, mixed-effects models, and survival analysis, etc.
• Proficiency in R and/or SAS for data management, analysis, and reproducible reporting; familiarity with Quarto or R Markdown.
• Demonstrated ability to work independently, manage multiple project deliverables simultaneously, and meet deadlines with minimal supervision.
• Exceptional attention to detail and commitment to analytical accuracy and reproducibility.
• Strong organizational skills and meticulous documentation habits.
• Excellent written and oral communication skills; ability to present statistical findings clearly to non-statistician audiences.
• Collaborative mindset and strong interpersonal skills; ability to work effectively as part of a multidisciplinary research team.
• Genuine intellectual curiosity and enthusiasm for continued learning in statistics, methodology, and clinical research.
   

• Master's degree in Statistics, Biostatistics, or a closely related quantitative field (e.g., Data Science with strong statistical training).
• Experience analyzing longitudinal, clustered, or otherwise complex data structures.
• Experience with omics data analysis (e.g., genomics, proteomics, or metabolomics) is a notable advantage.
• Experience with REDCap, Qualtrics, or similar electronic data capture systems.
• Proficiency in Python; experience with data visualization tools such as ggplot2, Plotly, Tableau, or R Shiny.
• Prior experience contributing to the writing of manuscript methods/results sections or statistical sections of grant proposals.
• Familiarity with version control (Git/GitHub) for collaborative code management.
• Knowledge of HIPAA, GCP, or other clinical research regulatory frameworks is a plus.
   

Michigan Medicine is one of the largest health care complexes in the world and has been the site of many groundbreaking medical and technological advancements since the opening of the U-M Medical School in 1850. Michigan Medicine is comprised of over 30,000 employees and our vision is to attract, inspire, and develop outstanding people in medicine, sciences, and healthcare to become one of the world?s most distinguished academic health systems.  In some way, great or small, every person here helps to advance this world-class institution. Work at Michigan Medicine and become a victor for the greater good.

What Benefits can you Look Forward to?

• Excellent medical, dental and vision coverage effective on your very first day
• 2:1 Match on retirement savings

Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes.

Hybrid work schedule with flexibility; full-time, regular appointment.

Domino Farms

This position is term-limited for about 2 years with the possibility of renewal based on need and available funding. At the end of the stated term, your appointment will terminate and will not be eligible for Reduction-in-Force (RIF) benefits. This term-limited appointment does not create a contract or guarantee of employment for any period of time as you will remain subject to disciplinary or other performance measures, up to and including termination, at the will of the University in accordance with existing University policy and standards for employee performance and conduct.

Michigan Medicine is firmly committed to advancing inclusion, diversity, equity, accessibility, and belonging, which are core to the culture and values of the Medical School Office of Research. Our community supports recruiting and cultivating a diverse workforce as a reflection of our commitment to serve the diverse people of Michigan and the world. We strive to create a work culture where each team member feels respected, valued, and safe. 

Michigan Medicine conducts background screening and pre-employment drug testing on job candidates upon acceptance of a contingent job offer and may use a third party administrator to conduct background screenings.  Background screenings are performed in compliance with the Fair Credit Report Act. Pre-employment drug testing applies to all selected candidates, including new or additional faculty and staff appointments, as well as transfers from other U-M campuses.

Job openings are posted for a minimum of seven calendar days.  The review and selection process may begin as early as the eighth day after posting. This opening may be removed from posting boards and filled anytime after the minimum posting period has ended.

The University of Michigan is an Equal Opportunity Employer. We are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants, including protected veterans and individuals with disabilities.