Bioinformatics Analyst I

Summary

The Bioinformatics Analyst I will analyze and integrate multi-modal molecular signatures in normal human and disease populations using bioinformatics and computational techniques and concepts. The job will include both deployment and development of state-of-the art analysis pipelines. Analysis will further incorporate advanced data science techniques such as deep learning and classification to identify potential disease drivers or biomarkers, repurposable drugs, and novel clinical associations of molecular profiles.

Job Duties

• Epigenomics. The analyst will process DNA methylation and histone modifications ChIP-Seq data, both in bulk tissue and in single-cell experiments. The analysis will determine differential epigenomic features, associate them with nearby genes, then assess enriched pathways.
• RNA-Seq. The analyst will map bulk RNA-seq data and quantify gene expression using cluster computing. The analyst will detect differentially expressed genes using multiple R analysis packages, run pathway enrichment, and generate visualizations including heatmaps.
• Single cell RNA-Seq and ATAC-Seq. The analyst will map and quantify single cell RNA-Seq and single cell ATAC-Seq data using cluster computing. Cell subpopulations will be indentified and characterized, and gene signatures and enriched pathways will be generated for individual cell types. Visualizations of cell types, gene markers, enriched pathways will be generated.
• MS Metabolomics. The candidate will normalize and assess the quality of MS Metabolomics and Lipidomics data. The analyst will analyze MS Metabolomics data using both parametric and non-parametric methods and generate both metabolic signatures and visualizations including heatmaps and boxplot for different experimental groups.
• RPPA Antibody Proteomics. The analyst will help the RPPA staff design antibody array, help with image analyis, assess quality control, process and normalize the RPPA data, generate reports for the RPPA core customers. The analyst will further analyze antibody proteomics datasets using both parametric and non-parametric approaches.
• Integrative analysis will integrate multiple omics platforms applied in the BCM cores and data publicly available via repositories such as NCBI GEO, Metabolomics Workbench, or Proteomics Workbench. The analysis will meet users and explain analysis and integration strategies employed, and assist also with preparation of quality figures for manuscripts and grant submissions. Analysis will further incorporate advanced data science techniques such as deep learning and classification to identify potential disease drivers or biomarkers, repurposable drugs, and novel clinical associations of molecular profiles.
• The Bioinformatics group will provide training and compute resources for the analysis, and regular guidance on the projects performed.
• Reviews existing multimodal omics signatures, publicly available datasets, propose and execute integrative analysis. Interprets results from similarity searches and integration of investigator and publicly available datasets.

Minimum Qualifications

• Bachelor's degree in Genetics, Biology, Bioinformatics, Biostatistics, Computational Biology, Computer Science, or a related field.
• No experience.

Preferred Qualifications

• Master's degree in a related field or Ph.D.
• Python/R programming, bioinformatics analysis of RNA-Seq, ChIP-Seq, pathway analysis, Unix/Linux, PBS or SLURM cluster based computing.
• R/Shiny / JavaScript/Django web development, database management, Machine Learning

Baylor College of Medicine is an Equal Opportunity/Affirmative Action/Equal Access Employer.