Bioinformatics program developer

OSDR and GeneLab Overview

NASA’s Open Science Data Repository (OSDR) is home to biological data and respective metadata from space-relevant experiments, including both physiological data (via the Ames Life Science Data Archive, ALSDA) and ‘omics data (via GeneLab). The primary goal of OSDR is to increase collaborative scientific data sharing and analysis leading to more rapid scientific advancement. Consistent with this goal, NASA GeneLab’s Data Processing (DP) team works with the scientific community to develop and maintain ‘omics data processing pipelines and workflows, then use the consensus pipelines to process all ‘omics data hosted on OSDR. NASA’s GeneLab project is seeking a talented, bioinformatics program developer to develop, manage, and run ‘omics data processing pipelines and workflows.

Position Summary

Blue Marble Space Institute of Science is seeking a bioinformatics program developer with extensive experience processing large-scale epigenomics, genomics, transcriptomics, proteomics, and/or metabolomics data, including both long- and short-read sequence data to support NASA GeneLab. The developer will support the data processing team in developing, maintaining, and running standard pipelines and workflows for processing sequence data and other omics datatypes from space biology experiments. An ideal candidate will have experience developing, installing, and running bioinformatics software and workflows on a high performing computing cluster, and support the space biology community with data processing-related questions. The position can be fully remote/virtual or has the option to be on-site at NASA Ames Research Center. The stipend range for this position is $112,000 – 122,000. Compensation will depend on education level and experience.

Essential Duties and Responsibilities

• Process and analyze biological data using various bioinformatics software and statistical methods

• Design, develop, and maintain various pipelines for processing bioinformatics data including (but not limited to) bulk RNAseq, single cell RNAseq, spatial transcriptomics, methylation sequencing, amplicon, metagenomics sequence data, and proteomic data such as GC/MS data

• Design and develop data processing workflows using open-source workflow software (e.g. nextflow)

• Create, maintain, and update scripts to automate the validation and verification of processed data generated from each step of the processing pipelines

• Create, maintain, and update pipeline and workflow documentation on the GitHub platform

• Support user questions on analysis pipelines, tool installations, and processed data

• Write technical documents and conduct training

• Create and document all actions, practices, procedures, and processes, and create troubleshooting documentation and Standard Operating Procedures

• Perform other duties and assist with special projects and installments as needed

The selected candidate will act as a bioinformatics Subject Matter Expert and will be expected to assist with troubleshooting the most complex situations in person or virtually with non-technical personnel.

Required Education/Experience

The candidate must be authorized to work in the United States. The incumbent shall have a Bachelor’s degree in Computer Science, Bioinformatics, Statistics, Microbiology, Genetics or a related field and 5+ years of related experience, or a Master’s degree with 2+ years of related experience, or a Ph.D.. The incumbent must perform job duties in one of the following states: CA, WA, CO, DE, PA, NY, TX.

Required Skills/Training:

• Expertise in programming and workflow languages for bioinformatics (R, bash, python, and nextflow) and Linux operating system

• Proficiency in basic omics data structure, algorithms, and statistical methods

• Expertise in the use of bioinformatics tools and database resources for various model organisms

• Relevant work experience in processing and analyzing transcriptomics data (bulk RNAseq, single cell RNAseq, spatial transcriptomics) and epigenomics data (enzymatic and bisulfite methylation sequencing data), including both short- and long-read data

• Familiar with software development best practices and various stages in the DevOps cycle including version control (i.e., GitHub), testing frameworks, continuous integration/continuous deployment (i.e., GitHub, Action, Jenkins), work-flow managers (i.e., nextflow), monitoring and collaboration

• Experience in applying appropriate data science techniques (e.g., statistical analysis and modeling, machine learning, prediction, and validation frameworks) to analyze a wide range of biological data (e.g., animal, in planta, NGS) is strongly desired

• Experience using and configuring Amazon Web services (AWS) and cloud-based systems

• Ability to function in a fast-paced environment with minimal supervision

• Must possess organizational, multitasking and prioritization skills

• Ability to communicate effectively and have excellent team and collaborations skills

• Flexibility to support mission priorities

• Attention to detail and follow-through

Desired Education, Experience, Skills or Training:

• Strong background and experience in statistics and statistical models and algorithms commonly used in analysis of life science data

• Relevant work experience in processing and analyzing variant call, GWAS, proteomics, and metabolomics data

• Experience with space biology research

• Installing, configuring, and maintaining high performance computing tools

• Experience with compute cluster job management tools (e.g. Slurm)