Research Scientist, AI​/ML Biologics

We are seeking an innovative Research Scientist specializing in Artificial Intelligence and Machine Learning (AI/ML) to support computational drug discovery initiatives across multiple therapeutic modalities. This role will focus on developing predictive and generative modeling approaches to accelerate the design, optimization, and evaluation of biologics, oligonucleotides, and related therapeutic platforms.

The ideal candidate will combine deep expertise in machine learning, computational biology, and therapeutic discovery with a passion for applying data-driven approaches to solve complex scientific challenges. This position offers the opportunity to collaborate with multidisciplinary teams and contribute to cutting-edge research programs at the intersection of biology, chemistry, and AI.

• Design and implement advanced AI and machine learning approaches to support therapeutic discovery and optimization.
• Develop and refine predictive models for sequence-based therapeutic design, activity prediction, and candidate prioritization.
• Build and deploy machine learning workflows for the optimization of biologics, antibodies, oligonucleotides, and other therapeutic modalities.
• Apply deep learning, generative AI, and protein language models to develop novel approaches for therapeutic design and discovery.
• Develop computational methods to model molecular interactions, sequence-function relationships, and structure-function relationships.

We are seeking an innovative Research Scientist specializing in Artificial Intelligence and Machine Learning (AI/ML) to support computational drug discovery initiatives across multiple therapeutic modalities. This role will focus on developing predictive and generative modeling approaches to accelerate the design, optimization, and evaluation of biologics, oligonucleotides, and related therapeutic platforms.

The ideal candidate will combine deep expertise in machine learning, computational biology, and therapeutic discovery with a passion for applying data-driven approaches to solve complex scientific challenges. This position offers the opportunity to collaborate with multidisciplinary teams and contribute to cutting-edge research programs at the intersection of biology, chemistry, and AI.

• Design and implement advanced AI and machine learning approaches to support therapeutic discovery and optimization.
• Develop and refine predictive models for sequence-based therapeutic design, activity prediction, and candidate prioritization.
• Build and deploy machine learning workflows for the optimization of biologics, antibodies, oligonucleotides, and other therapeutic modalities.
• Apply deep learning, generative AI, and protein language models to develop novel approaches for therapeutic design and discovery.
• Develop computational methods to model molecular interactions, sequence-function relationships, and structure-function relationships.

• Build scalable and reproducible computational frameworks for data ingestion, feature engineering, model development, validation, and deployment.
• Curate, integrate, and harmonize internal and external datasets to support machine learning initiatives.
• Develop and evaluate sequence-, structure-, and chemistry-based features to improve model performance.
• Establish benchmarking strategies and validation frameworks to assess model accuracy, robustness, and scalability.
• Maintain well-documented and reproducible analytical workflows, codebases, and scientific pipelines.

• Support therapeutic discovery efforts through data-driven prediction, prioritization, and decision-support tools.
• Partner with experimental scientists to validate model predictions and refine computational approaches.
• Evaluate and implement emerging AI, machine learning, and computational biology technologies to enhance research capabilities.
• Collaborate closely with biologists, chemists, computational scientists, and data engineers to advance scientific objectives.
• Communicate scientific findings, technical approaches, and recommendations to cross-functional stakeholders.
• Contribute to scientific strategy discussions and innovation initiatives.
• Perform additional scientific and computational research activities as needed.

• PhD in Computational Biology, Computational Chemistry, Machine Learning, Bioinformatics, Biomedical…