The posting
Job Summary
The bioinformatician will develop algorithms and computational resources to analyze and interpret how dysregulated RNA splicing contributes to human disease. Working with the PI and experimental collaborators, the bioinformatician turns biomedical questions into algorithmic approaches, implements them as tested, reproducible software, and applies them to bulk, single-cell, spatial transcriptomic data. The bioinformatician takes scientific ownership of method development, taking novel approaches through benchmarking to peer-reviewed publication and open release. Results are interpreted mechanistically, linking splicing changes to their regulators and functional consequences, and used to propose and prioritize experimental validation. The bioinformatician presents findings internally and externally and works independently with limited supervision. The bioinformatician assists and collaborators with other lab members to advance their research, and helps update and maintain widely used pipelines and tools.
Key Responsibilities & Essential Functions
· Design, implement, test, and benchmark novel algorithms and statistical or machine-learning models for splicing analysis, such as event detection and quantification, differential splicing, isoform-level analysis, and prediction of variant effects on splicing.
· Lead method development through to manuscript-ready stage, serving as co-author on resulting publications.
· Apply these methods to patient-derived, model-system, and public datasets, bulk and single-cell, to identify disease-associated splicing alterations, their upstream drivers (trans-acting factors and cis-regulatory variants), and their downstream consequences.
· Integrate splicing data with other modalities, such as genomic variation, long-read transcriptomics, epigenomic, and proteomic data, to support mechanistic interpretation.
· Build version-controlled, containerized, documented pipelines (Nextflow) and release tools openly so that analyses are reproducible by external groups.
· Work with the PI and experimental collaborators to define questions, design validation experiments, and interpret results.
· Present pipelines, methods, and results at internal meetings and external conferences, and contribute to manuscripts and grant applications.
· Keep current with the splicing, RNA biology, and computational genomics literature, and mentor junior staff and trainees as needed.
Other Knowledge, Skills, and Abilities
- BS degree in Bioinformatics or relevant biological sciences degree + five years of professional bioinformatics work experience or MS degree in Bioinformatics or relevant biological sciences degree. Works under close supervision.
- PhD degree in bioinformatics, biology or a related field preferred
- Deep knowledge of RNA biology and genomics, including splicing mechanisms, cis-regulatory elements, and splicing factors.
- Demonstrated experience with splicing analysis of transcriptomic data, including the limits and failure modes of these tools.
- Proficiency in Python, R, and Bash, and experience with workflow management Nextflow).
- Experience developing algorithms in machine learning, statistics, or genomics, evidenced by novel methods or substantial extensions of existing ones.
- Software engineering practice: version control, automated testing, containerization, and documentation.
- Experience with single cell and/or spatial transcriptomics.
- Ability to read, critique, and apply the primary literature in fields related to current projects.
- Ability to lead projects and work independently with limited supervision.
- Clear written and oral communication of methods and results to scientific audiences.
- First-author publication in a peer-reviewed journal.
- Experience with HPC or cloud compute environments at scale.
- Experience mentoring students or junior colleagues.
- Experience with human cohort or controlled-access data (TCGA, GTEx, dbGaP) and splicing QTL analysis is a plus.
- Experience with deep-learning models of sequence-to-splicing relationships is a plus.
- Experience with long-read RNA sequencing and isoform-level analysis is a plus.
- Prior projects on splicing in a disease context, including identification of disease-associated splicing events or splicing-factor dysregulation is a plus.
Minimum Requirements
Minimum Education Required: Bachelor's degree
Preferred Education: Doctorate degree
Minimum Experience Required: 2 years
Pay Range: $65,018 - $108,857, pay determined by years of experience
About JAX:
The Jackson Laboratory is an independent, nonprofit biomedical research institution with a National Cancer Institute-designated Cancer Center and nearly 3,000 employees in locations across the United States (Maine, Connecticut, California, New York, Florida), Japan and China. Its mission is to discover precise genomic solutions for disease and empower the global biomedical community in the shared quest to improve human health.
Founded in 1929, JAX applies over nine decades of expertise in genetics to increase understanding of human disease, advancing treatments and cures for cancer, neurological and immune disorders, diabetes, aging and heart disease. It models and interprets genomic complexity, integrates basic research with clinical application, educates current and future scientists, and provides critical data, tools and services to the global biomedical community. For more information, please visit www.jax.org.
EEO Statement:
The Jackson Laboratory provides equal employment opportunities to all employees and applicants for employment in all job classifications without regard to race, color, religion, age, mental disability, physical disability, medical condition, gender, sexual orientation, genetic information, ancestry, marital status, national origin, veteran status, and other classifications protected by applicable state and local non-discrimination laws.
