Job Summary

This postdoctoral research fellow will join a sports medicine research and musculoskeletal research lab that currently focuses on clinical trials, epidemiology, outcomes, and genetics research on patients with rehabilitation and orthopedic conditions such as rotator cuff tears and glenohumeral osteoarthritis that cause shoulder pain. This position will work on multiple studies/projects including a large multi-center study on the genetic epidemiology of rotator cuff tears called cuffGEN. This large study will collect patient outcomes, saliva and tissue samples to determine the genetic variants associated with rotator cuff tendon disorders. The fellow will also work on ARC which is a multi-center randomized clinical trial on operative versus non-operative treatment for rotator cuff tears.

As a postdoctoral research fellow within PM&R /Michigan Medicine at the University of Michigan, the candidate will have access to significant professional development opportunities, mentorship, and analytical support. In particular, the Institute for Healthcare Policy and Innovation (IHPI) and the MICHR support multiple grant-writing and career development workshops, training opportunities and internal grants.

In addition to the technical and scientific writing skills, ideal candidates for this position should have excellent analytical and problem-solving skills and must be thriving in both a team and individual environment. Since the candidate will be leading the effort in these projects, he/she must also have strong organizational and communication skills. Candidates for this position should be internally motivated, detail-oriented, intellectually curious, with a desire to grow their skill-set.

Responsibilities*

The selected candidate will be expected to design experiments in an independent fashion, analyze data, develop new research methodologies, and prepare research papers. While funding is currently available for a one-year position, the candidate will be strongly encouraged to apply for additional funding. To complete these responsibilities, the ideal candidate should have excellent verbal and written communication skills, attention to detail, and demonstrated computer efficiency. In addition, the candidate should have strong organizational skills, the ability to successfully manage competing priorities, the ability to anticipate needs and follow through on the completion of tasks, and the ability to work well independently as well as collaboratively in a team environment.

Perform large-scale quality control (QC), phasing and imputation of genotypic data, population structure testing, association studies, meta-analysis and fine mapping
Contribute to building, benchmarking, and maintenance of bioinformatics pipelines for high-throughput genomic data analysis in high-performance computing (HPC) and cloud environments
Harmonize and maintain diverse datasets and their associated metadata
Perform QC and normalization on transcriptomics data
Carry out downstream analysis such as differential gene expression analysis, gene set enrichment analysis, cell-type annotation, cell-cell communication analysis and pathway analysis on bulk, single-cell and spatial transcriptomics data
Prepare and maintain technical documentation for data and analysis files.
Summarize, interpret, and present results in written, tabular and visual formats for reports, manuscripts, and presentations.
Assist in the writing and editing of reports, abstracts, manuscripts, conference presentations, and grant proposals.
Write research papers and review images
Participate as a team member in discussions on analysis and improvement of data collection, quality of data analyses, programming, and documentation.

Required Qualifications*

Doctoral degree in computational biology or bioinformatics

Desired Qualifications*

In-depth knowledge of genome-wide association studies, interpretation, and application of computational research on large multivariate datasets
Familiarity with high-performance computing systems and open-source bioinformatics tools including PLINK, SNPTEST, IMPUTE2, BEAGLE, UCSC Genome Browser, Michigan Imputation Server, Seurat, edgeR and limma
Proficienct in statistical programming and data manipulation using R and Python
Team-oriented with excellent written and verbal communication skills
Ability to organize and execute multiple projects simultaneously
Familiarity with publicly available data resources such as 1000 Genomes, GTEx and ENCODE

Work Locations

North Campus Research Complex (2800 Plymouth Road)

Modes of Work

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.

Additional Information

This is a one year term-limited position with an extension possible. 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.

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.