Description
Conduct research using bioinformatics theory and methods across pharmaceuticals, biotechnology, computational biology, and medical informatics. Design databases, algorithms, and software to process, analyze, and interpret genomic and other biological data for discovery and clinical applications.
- • Recommend new systems and processes to improve research and data operations.
- • Stay current with new biochemistries, instrumentation, methods, and software through literature and conferences.
- • Partner with marketing, business development, and operations to align product development with scientific insights.
- • Collaborate with software engineers to design and enhance bioinformatics software.
- • Evaluate and benchmark new and updated bioinformatics tools.
- • Build statistical and computational tools for genetic analysis, gene expression measurement, and functional annotation.
- • Generate summary statistics and quality metrics for human genome datasets.
- • Train researchers and staff in the selection and use of bioinformatics tools and workflows.
- • Improve user interfaces and usability of bioinformatics software and databases.
- • Lead and mentor technicians and IT staff applying tools in proteomics, transcriptomics, metabolomics, and clinical informatics.
- • Develop or customize software applications to meet project-specific scientific needs.
- • Design data models and develop scalable databases.
- • Create and maintain web-based bioinformatics tools and portals.
- • Design and apply algorithms, including supervised and unsupervised machine learning, dynamic programming, and graph algorithms.
- • Create novel computational approaches and analytical pipelines to meet research goals.
- • Compile and curate data for gene expression profiling, genome annotation, and structural bioinformatics.
- • Communicate research results through presentations, publications, and technical reports.
- • Integrate and manage public, commercial, and proprietary genomic, proteomic, and other omics databases.
- • Consult with researchers to define problems, recommend technology solutions, and determine computational strategies.
- • Analyze large molecular datasets, such as NGS, microarray, genomic sequence, or proteomics data, for clinical and basic research.
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Last reviewed: Jan 2026
