Bioinformatics Co-op (Fall 2026)

Role Summary

Wave needs a highly motivated and detail-orientated individual to work in the areas of bioinformatics, computational biology and human genetics in support of Wave’s drug discovery programs. The candidate will design and execute sequence-based machine learning projects that generate critical information for drug discovery and target assessment. The candidate will create and deploy data and test hypotheses related to human genetics and bioinformatics. The candidate will build and use the next generation of human genetics and bioinformatics tools for the development of oligonucleotide therapeutics. The candidate should have a strong coding and software development background and a willingness to work in an interdisciplinary team of chemists, biologists, and software developers.

Responsibilities

• Design and build pipelines that process and analyze related data, store summary results and integrate with the corporate ELN
• Build applications to support bioinformatics and human genetics pipelines in R (shiny) and Python (streamlit)
• Develop, deploy, manage, and run applications using Docker containers
• Contribute to best practices for Wave’s storage-and-compute scalability of large bioinformatics datasets
• Develop pipelines that determine mapping coordinates and homology of oligonucleotides to genomes and transcriptomes
• Espouse best practices for version control for developed software (Git)

Qualifications

• Discovery and development of oligonucleotide therapeutics is a plus
• Working with high-performance compute environments

Skills

• Experience with common human genetics resources and techniques
• Deployment of interactive applications from scripting languages like R and Python (Shiny and streamlit)
• Experience with relational databases; hands-on experience with MySQL is a plus
• Experience in common NGS analyses tasks such as mapping reads, quantification of gene expression, and/or variant calling
• Experience with common bioinformatics tools like Samtools, GATK, Bowtie, HISAT2, BLAST, htseq-count, DESeq, Salmon, STAR, or Subread
• Knowledge of Illumina sequencing data analysis; PacBio and/or Nanopore sequencing is a plus
• Familiarity with UNIX computing environment and proficiency in either Python or R scripting; experience with Docker and Nextflow pipeline is strongly recommended
• Ability to communicate findings of NGS data to a general scientific audience in both oral and written forms