ALS Research Statistician

25 May 2019
End of advertisement period
26 Jul 2019
Contract Type
Full Time

What You'll Do

We are searching for a statistician or biostatistician to work with a dynamic amyotrophic lateral sclerosis (ALS) research group comprised of neurologists, immunologists, basic scientists, biostatisticians, environmental scientists, epidemiologists, bioinformaticians, and data managers. This individual will be working with multiple datasets, including longitudinal clinical data, immunophenotyping, environmental exposure data, and various –omics datasets, e.g. genomic, transcriptomic, metabolomic, and epigenomic.


The statistician will work closely with the research team to:

Provide guidance for study design issues.

Perform power calculations and estimating 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.

Conduct computer programming as needed for completion of other tasks.

Prepare and maintain technical documentation of data management and analysis files.

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.

Other duties as assigned.

Skills You Have

Comfort with longitudinal data analysis and –omics data is a must. Experience with the analysis of chemical mixtures, machine learning, and artificial intelligence is a plus.

Required Qualifications*

Bachelor’s degree in biostatistical, statistical, or related field.

1-3 years' processional experience.

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.

Strong programming knowledge using high-level programming language

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*

Advanced degree (PhD) in biostatistical, statistical, or related field.

Desire to learn new programming and statistical skills

Familiarity with medical terminology

Experience with the analysis of chemical mixtures, machine learning, and artificial intelligence

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.