Bioinformatician I (RNA Splicing)

Location: Farmington, Connecticut, United States

Pay range: $65,018–$108,857 per year; pay is determined by years of experience.

Company

hirify.global is an independent, nonprofit biomedical research institution and National Cancer Institute-designated Cancer Center focused on genomic solutions for disease and biomedical research.

What you will do

• Design, implement, test, and benchmark algorithms and statistical or machine-learning models for RNA-splicing analysis, including event detection, differential splicing, isoform analysis, and variant-effect prediction.
• Apply methods to patient-derived, model-system, and public bulk, single-cell, and spatial transcriptomic datasets to identify disease-associated splicing changes, regulators, and functional consequences.
• Integrate splicing data with genomic variation, long-read transcriptomics, epigenomic, and proteomic data for mechanistic interpretation.
• Build version-controlled, containerized, documented Nextflow pipelines and openly release reproducible tools.
• Lead methods through benchmarking and manuscript-ready publication, contribute to manuscripts and grants, and present results internally and externally.
• Collaborate with the PI and experimental researchers to define questions, design validation experiments, interpret results, maintain pipelines, and mentor junior staff or trainees.

Requirements

• Bachelor’s degree in Bioinformatics or a relevant biological sciences field with five years of professional bioinformatics experience, or a master’s degree in Bioinformatics or a relevant biological sciences field; minimum two years of experience required.
• Deep knowledge of RNA biology and genomics, including splicing mechanisms, cis-regulatory elements, and splicing factors.
• Demonstrated experience analyzing splicing in transcriptomic data, including knowledge of tool limitations and failure modes.
• Proficiency in Python, R, and Bash, with experience using Nextflow.
• Experience developing algorithms in machine learning, statistics, or genomics, demonstrated through novel methods or substantial extensions of existing methods.
• Experience with version control, automated testing, containerization, and documentation.
• Experience with single-cell and/or spatial transcriptomics, HPC or cloud computing at scale, and human cohort or controlled-access data.
• Ability to read, critique, and apply primary literature; lead projects independently with limited supervision; and communicate methods and results clearly to scientific audiences.
• First-author publication in a peer-reviewed journal.

Nice to have

• PhD in bioinformatics, biology, or a related field.
• Experience with splicing QTL analysis, deep-learning models of sequence-to-splicing relationships, long-read RNA sequencing, isoform-level analysis, or disease-focused splicing projects.

Culture & Benefits

• Work in an independent nonprofit biomedical research institution with a mission focused on improving human health.
• Collaborate across computational, experimental, and clinical research programs.
• Contribute tools and methods to the global biomedical research community through open release and peer-reviewed publication.
• The institution has nearly 3,000 employees and locations across the United States, Japan, and China.