Bioinformatics Analyst I – CPDM

Job Description:

• Develop computational and systems strategies for data capturing, storing, searching and analyzing across various high-throughput genomic, transcriptomic, epigenomic, and molecular data.
• Design and implement strategy to synchronize databases from various collaborating partners to generate an integrated database-driven web resources amendable for robust data exploration, visualization, and discovery applications.
• Develop automation in capturing and creating data, reports, and summaries from electronic clinical and research records and databases.
• Support the development of bioinformatics web applications.
• Modify database designs to meet the requirement of new clinical/research projects.
• Manage and maintain data update on project databases.
• Support the development of data processing and analysis pipelines for Next Generation Sequencing data.

• BS in Computer Science, Engineering, Bioinformatics, Data Science, or related fields. 1-2 years of relevant experience is required.
• Basic understanding of NSG data outputs, data management and analysis. Background in Molecular Biology and Genetics is a plus.
• Experience with data collection and management, and database design and management.
• Experience with standards on clinical and research data procedures.
• Familiar with data management software/application such as REDCap, DatStat, LIMS, and Tableau.
• Experience with programming in Python and R and familiarity with MATLAB, Java, C++, Perl, web-development, and database query through SQL
• Experience in developing pipelines in analyzing NGS data and familiarity with common bioinformatics resources such as bwa, BEDtools, GATK, IGC and cancer genomics resources such as cBioPortal.

Requeriments :

• Technical Bachelor

Skills :

• Bioinformatics
• Database design
• Genetics
• genomic
• LIMS
• molecular biology
• Next Generation Sequencing
• Programing in C++
• Programing in Python
• Programming in Java
• Programming in Matlab
• Programming in PERL
• Programming in R
• SQL

Areas :

• Bioinformatics

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