AbbVie is seeking to bridge the gap between genomic evidence and safety outcomes in pharmaceutical development by leveraging AI-driven methodologies
Requirements
- PhD in Computational Biology, Bioinformatics, Computer Science, Human Genetics, Toxicology, or related field
- Strong programming skills in Python with experience in data manipulation, analysis, and machine learning libraries
- Demonstrated experience in applying advanced AI/ML methods to biological problems
- Experience with database querying, management systems, and data extraction techniques for large datasets
- Knowledge of natural language processing (NLP) and/or large language models (LLMs)
- Experience with genomic data analysis, including variant interpretation or population genetics
- Proficiency in statistical analysis and interpretation of complex biological datasets
Responsibilities
- Identify, curate, and process internal and external genetic and safety-related datasets, applying sophisticated data science methodologies
- Design and implement agentic AI systems capable of autonomous data querying, extraction, and interpretation across traditionally siloed safety and genomic domains
- Develop advanced data harmonization techniques and standardized ontologies to enable integration of genetic, preclinical, and clinical safety datasets
- Implement graph-based retrieval-augmented generation (RAG) methods to enhance knowledge extraction and information synthesis
- Develop cross-pathway analytical methods using AI to predict safety outcomes for multiple targets and combination therapies
- Collaborate with research teams and data scientists to design data-driven strategies using machine learning/AI methods that support discovery and preclinical safety studies
- Generate and validate experimental hypotheses derived from AI models in collaboration with in vitro teams
Other
- Excellent communication skills, with ability to translate complex computational findings to diverse stakeholders
- Track record of scientific creativity and problem-solving in research activities
- Builds strong relationships with peers and cross functionally with partners outside of team to enable higher performance
- Learns fast, grasps the 'essence' and can change course quickly where indicated
- Raises the bar and is never satisfied with the status quo
