The Salomonis lab within BMI develops new integrative solutions for single-cell and bulk genomics assays with an emphasis on understanding cellular heterogeneity in healthy tissue systems and disease. This includes various computational approaches for single-cell transcriptomics and multimodal analysis. The Bioinformatics Analyst works in close collaboration with our experimental collaborators on multiple inter-connected projects to identify novel transitional cell-states in stem and progenitor populations, develop computational strategies to isolate cell populations CITE-Seq (single-cell transcriptomes with surface-linked antigen expression), track cells during differentiation, dissect underlying gene regulatory networks using multi-omics and multimodal single-cell approaches, evaluating and improving existing computational approaches and working with a team of analysts and biology domain experts to create new molecular models of development and disease, with an emphasis on immunobiology and cancer. The ideal candidate will have significantly contributed to prior publications, demonstrated “out-of-the-box” thinking, excellent communication skills, demonstrated research independence, and excellent programming experience.
- 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.
For specific questions, please contract Dr. Nathan Salomonis at email@example.com or visit his website: (https://www.cincinnatichildrens.org/research/divisions/b/bmi/labs/salomonis)
Experience & Education Requirements
- Master’s degree in a related field
- 2 – 5 years of work experience in a related job discipline
- Experience with diverse genomics data type (RNA-Seq, genome-sequencing, ATAC-Seq)
- Experience programming in Python and cluster-compute environments
- Background in statistics and/or software development and/or Machine learning/API
- Bachelor’s degree in a related field