How to Apply

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, outline skills and experience that directly relate to this position, and list 3 references.

Summary

We are searching for a biostatistician postdoctoral research fellow to work with a dynamic neurodegeneration research group comprised of neurologists, immunologists, basic scientists, biostatisticians, environmental scientists, epidemiologists, bioinformaticians, and data managers. This individual will work with multiple datasets, longitudinal clinical data, survival data, immunophenotyping, and environmental exposure data related to neurodegenerative diseases, such as amyotrophic lateral sclerosis (ALS). Experience with the analysis of chemical mixtures, machine learning, and artificial intelligence is a plus.

Responsibilities*

The biostatistician/fellow will work closely with the research team to:

• Provide guidance for study design issues.
• Perform power calculations and estimate sample size.
• Write, test, and implement programs using R, Stata, or SAS to clean, manage, merge, and analyze large, complex datasets.
• Implement methods to ensure data quality and replication of results.
• Develop and draft specific plans for data management and analysis.
• Conduct appropriate data management and analysis.
• Summarize, interpret, and present results in written, tabular, and visual formats.
• Assist in the writing and reviewing of statistical methods in manuscripts and grant proposals.
• Prepare annotated statistical code and logfiles for submission with manuscripts to journals.
• Participate as a team member in discussions on data collection, management, and analysis.

Required Qualifications*

• Doctoral degree in biostatistics, statistics, or related field.
• Ability to draft and do data management and analysis plans based on study design.
• Ability to solve problems with data management and analysis.
• Working knowledge of concepts and methods in epidemiology and biostatistics.
• Experience working with complex data structures and linkages between data sources.
• Proven ability to write clear and concise technical documentation, summaries of various methodologies, and descriptions of statistical results.
• Excellent communication, both oral and written in the English language.
• Ability to prioritize, organize, and efficiently work on multiple projects at the same time.
• Flexibility and ability to work independently and collaboratively with multiple researchers.
• Ability to be consistently and extremely detail oriented.

Desired Qualifications*

• Desire to learn new programming and statistical skills
• Familiarity with medical terminology
• Experience with data integration, the analysis of chemical mixtures, machine learning, and artificial intelligence, please indicate relevant experience on your cover letter.
• Prior experience with: (1) ?omics datasets, e.g. genomic, transcriptomic, metabolomic, and epigenomic or (2) geospatial data is a plus. While this prior experience is not required for this position, if you have these skills, please indicate on your cover letter.

Background Screening

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.

Application Deadline

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.

U-M EEO/AA Statement

The University of Michigan is an equal opportunity/affirmative action employer.