Lead Analyst - Bioinformatics


The Grimes and Salomonis Labs are looking for an experienced Senior Bioinformatics Analyst to join our team of computational and experimental biologists, working to address fundamental challenges in the field of normal and malignant hematopoiesis. Our labs exploit cutting-edge omics tech to answer fundamental biological questions in hematopoiesis, marrow failure and myeloid leukemia. We develop new informatics tools when existing tools are insufficient to resolve data such as CITE-Seq, TEA-Seq, promoter capture Hi-C, ChiP-Seq, Cut&Run, CLIP-Seq, perturb-Seq and single-cell Iso-Seq. Our team works collaboratively, among investigators, postdoctoral researchers, graduate students and bio-informaticians to validate the existence of novel cell-populations using rigorous experimental isolation and functional characterization techniques and from prior published datasets (in silico). More about our science can be found here: PMID: 32494068, PMID: 30249787, PMID: 30243574, PMID: 29977015 and PMID: 27580035.

The ideal candidate will have:
  • Knowledge of state-of-the-art bioinformatics analytical methods coupled with the creativity and intelligence to advance beyond them.

  • Strong experience with RNA-Seq data analysis and downstream functional analysis toolkits.
  • Leadership abilities necessary to lead projects.
  • Ability to independently manage and synthesize data from multiple projects (data tracking, data summarization, results integration).
  • Interpersonal communication: Excellent verbal, written and interpersonal communication skills with ability to communicate with personnel at all levels of the organization.
  • Strong understanding of fundamental biological, disease and genomics concepts.
  • Prior experience with large-scale integrated genomics analyses (e.g. splicing, gene expression, single-cell, ChIP-Seq, regulatory sequence motif analysis).
  • Technology: Familiar with relational database concepts, and client-server concepts. Capable of working on Linux, Unix and Windows environments.
  • Biostatistical analysis and novel algorithm/methods implementation.
  • Proficient use of command-line programs and/or scripting in Python, R and/or other object-oriented languages such as C++ and Java.
  • Strong understanding of existing genomic databases, tools, and processes

  • Perform data analysis for research projects: Work collaboratively with research groups for the analysis of single-cell and bulk transcriptome datasets. Perform quality control, sequence alignment, gene and splicing statistical analyses and functional regulatory from next generation sequencing experiments. Integrate datasets across from different patients, disease states and across species. Evaluate the contribution of complex biological or technological covariates from large-scale genomic results (e.g., batch effects, sex). Evaluate results at the gene, pathway, and systems-level, integrating detailed biological knowledge at different steps in the analysis. Apply statistical analysis or machine learning analysis methods. Customize data visualization results using existing software toolkits (e.g., R, python). Prepares manuscript materials for publications and reports about research projects for presentation at scientific meetings.
  • Informatics operation: Applies existing software to support sequence alignment, inter-sample comparison, algorithm evaluation, data management, data retrieval, and web access. Document standard operating procedures based on best practice. Experience working with complex metadata and data/results documentation (provenance). Assists in developing tools to support unsupervised sample and gene heterogeneity analyses. Incorporates institutional resources and 3rd party software into specialized analysis workflows for the team and clients. Helps to maintain computational infrastructure and control the flow of samples and information for studies. Works closely with Biomedical Informatics department to leverage system, software and knowledge efficiencies.
  • Teamwork: Guides and advises less-experienced staff. Trains and supports staff, residents, fellows, and technologists. Communicate results outside of CCHMC.



• Masters degree in related field.
•5+ years of work experience in a related job discipline OR equivalent combination of education and experience

  • New PhD in a related field
  • Strong publication track-record
  • 3 years of directly related experience