Bioinformatics Analyst: Genomics Data & Algorithms

Washington University; Missouri; On-site; USD 24,000 - 40,000; Full time

Job summary

Washington University in St. Louis is seeking a researcher to assist with computational data analysis for omics-based datasets, manage and analyze large data sets, and help report methods and results.

The role involves collaboration within a research team and development of new algorithms to support studies. The position is based in Saint Louis, MO with a 40-hour work week and a focus on data-driven analysis in a laboratory environment, including physical activities and protective equipment as

Qualifications

• Bachelor’s degree or combination of education and/or experience may substitute for minimum education.
• No specific certification or professional license is required.
• No specific work experience is required.
• Skills listed are not required for all positions.

Responsibilities

• Assist research studies with implementation of existing algorithms and computer software for analyzing omics-based data sets (high-throughput, massively parallel genomic/proteomic/clinical).
• Assist with data management and analysis solutions that help store, investigate, and disseminate large data sets.
• Work with research team to develop new algorithms to support studies.
• Assist with reporting of methods, data and results.

Skills

Analytical Thinking

Bioinformatics Tools

Communication

Complex Data Analysis

Computational Biology

Critical Reasoning

Gene Expression Microarray

Genome Sequencing

Group Problem Solving

Human Genetics

Model Organism

Education

Bachelor’s degree

Tools

Bioinformatics Tools

Job description

Washington University in St. Louis is seeking a researcher to assist with computational data analysis for omics-based datasets, manage and analyze large data sets, and help report methods and results.

The role involves collaboration within a research team and development of new algorithms to support studies. The position is based in Saint Louis, MO with a 40-hour work week and a focus on data-driven analysis in a laboratory environment, including physical activities and protective equipment as