University Of Michigan-posted 7 months ago
Entry Level
Remote • Ann Arbor, MI
Educational Services

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 Michigan Institute for Clinical and Health Research 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.

  • Design experiments in an independent fashion
  • Analyze data and develop new research methodologies
  • Prepare research papers
  • 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
  • Doctoral degree in computational biology or bioinformatics
  • 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
  • Proficient 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
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