Bioinformatics Analyst II



Summary

The Bioinformatics Analyst II 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
  • RPPA Antibody Proteomics
  • Helps the RPPA staff design antibody array, helps with image analyses, assesses quality control, processes and normalizes the RPPA data, generates reports for the RPPA core customers.
  • Further analyzes antibody proteomics datasets using both parametric and non-parametric approaches.
  • RNA-Seq
  • Maps bulk RNA-seq data and quantify gene expression using cluster computing.
  • Detects differentially expressed genes using multiple R analysis packages, run pathway enrichment, and generate visualizations including heatmaps.
  • Single cell RNA-Seq
  • Maps and quantifies single cell RNASeq data using cluster computing.
  • Cell subpopulations will be identified 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.
  • 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.
  • Trains junior analysts, graduate students, and postdocs in specific analysis techniques as needed.


Minimum Qualifications
  • Bachelor's degree in Genetics, Biology, Bioinformatics, Biostatistics, Computational Biology, Computer Science, or a related field.
  • One year of relevant experience.


Preferred Qualifications
  • Master's or PhD are preferred.
  • 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.

5885

CA; CH

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