The bioinformatician will process biomedical data by utilizing/applying existing informatics/software resources/analysis methods on multiple computing platforms/in multiple programming languages, automating/managing repetitive tasks, developing small-scale software modules, assist in extracting/organizing/manipulating/annotating/visualizing/summarizing data from diverse data sources to aid knowledge discovery and inference process, and carry out custom bioinformatics tasks as required and specified by the senior staff and supervisors.

Responsibilities include: The bioinformatician will process biomedical data by utilizing/applying existing informatics/software resources/analysis methods on multiple computing platforms/in multiple programming languages, automating/managing repetitive tasks, developing small-scale software modules, assist in extracting/ organizing/ manipulating/ annotating/ visualizing/ summarizing data from diverse data sources to aid knowledge discovery and inference process, and carry out custom bioinformatics tasks as required and specified by the senior staff and supervisors. Implementation, application, maintenance, customization of available/known informatics resources and scientific software/data sources in multiple programming languages/platforms for research support. Developing front-ends for other analysis tools, visualization/compilation of results, facilitating generally defined routine data processing/migration/organization/management tasks, and building project-specific workflows implementing automated analysis steps. Investigation, customization, prototyping for new bioinformatics resources, and scientific software for biomedical data processing. Requires skills in multiple programming languages, databases, computational methods, scientific computing, large-scale data analysis, and heterogeneous biomedical data from multiple sources. Using software engineering skills towards creating reusable, modular, tested, version-controlled, shared repository oriented, professional-quality informatics/software/database resources. Designing, prototyping, evaluating innovative computational algorithms, data analysis, and statistical methods for biomedical data processing, interpretation and knowledge mining of data, computational algorithms, databases, scientific computing, large-scale data analysis. Suggesting/exploring alternative/multiple data processing approaches. Following scientific literature/manuscripts, investigating new biomedical data processing methods, trends, technologies, and paradigms relevant to biomedical informatics, providing feedback towards scientific findings, and contributing towards manuscripts/grants/research proposals and research planning. Attending/contributing to/presenting at internal/external scientific meetings/conferences Managing multiple bioinformatics collaborations/projects, mentoring junior staff. Strategic planning, organization, management, organization, utilization, and optimization of existing and future bioinformatics resources, skills, and needs. Interacting with PIs, researchers, and other bioinformaticians towards aligning/guiding the bioinformatics activities to maximize the organization's competitive advantage in biomedical research. Interacting with other research divisions, computing infrastructure staff, and outside academic/industrial partners.

PM21

• Bachelors/Masters Degree in Bioinformatics/Computer Science/Bioengineering/Computational Biology or related field.
• Must have at least 1-year post-graduation experience.
• Must have formal training or exposure to adaptive immunity analysis (MHC-driven immunity/peptide-MHC complex generation, etc)
• Experience in academic/industrial applied research environment in biomedical data analysis Experience in software development in multiple programming languages, such as Perl/C++/C/Python/Java, and derivatives for biological data analysis
• Experience in downloading/learning/applying software and database resources for custom analysis and building workflows
• Experience with Linux/UNIX/Mac OS X-based systems and developing shell scripts/command-line interfaces for data processing
• Formal training or exposure to computational biology/biological data analysis, such as gene expression, epigenetics, genotyping, sequencing, CGH, phylogeny, proteomics, or in the specific field needed by the duties Familiarity with various biomedical databases Experience with scientific computing and data visualization tools, such as MATLAB, R, etc., and understanding of basic statistics