Overview In this role, you apply AI/ML to accelerate discovery in ASO therapeutics and antibody research, working across multiple biologic modalities. You will collaborate with experimental teams to validate predictions and build scalable, reproducible computational workflows. The role blends de novo antibody discovery, sequence-aware ASO modeling, and generative protein design to drive multi-objective optimization. This is a hands-on, impact-focused position within a remote contract setting and cross-functional team.
Compensation / Benefits- health insurance
- health savings account
- retirement savings plan
- life and disability insurance
- paid leave
Responsibilities- Design and implement AI/ML methods for de novo antibody discovery
- Develop sequence-aware predictive models to prioritize ASO therapeutics based on exon-skipping response
- Fine-tune protein language models and develop generative protein design workflows
- Deploy ML methods for multi-objective optimization across antibodies, antigens, ADCs, and other biologics
- Build reproducible computational frameworks and curate/harmonize datasets
- Define robust sequence and structure features and establish model benchmarks
- Collaborate with experimental teams to validate predictions and integrate proprietary and open-source tools
- Maintain well-documented codebase and provide user guidance for cross-functional teams
Key requirements- PhD in a relevant field with at least three years of industry experience
- Strong background in oligonucleotide chemistry, antibody design, and computational modeling of antibody-antigen interactions
- Expertise in probabilistic and deep learning models
- Programming in Python, R, and SQL
- Experience with modern deep learning frameworks
- Familiarity with large-scale computing and cloud infrastructure
- Excellent communication and teamwork skills
- strong communication
- collaboration
- continuous learning
- Python
- R
- SQL
