Postdoctoral Fellow, Computational Genetic and Safety Data Science

We are seeking a Postdoctoral Fellow to develop AI-driven methodologies to bridge the gap between genomic evidence and safety outcomes, addressing a critical challenge in pharmaceutical development.

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
• Demonstrated ability to develop data visualization tools and interfaces for biological data representation
• Excellent communication skills, with ability to translate complex computational findings to diverse stakeholders
• Track record of scientific creativity and problem-solving in research activities

Benefits

• Paid time off (vacation, holidays, sick)
• Medical/dental/vision insurance
• 401(k)
• Short-term incentive programs