Scientist, Machine Learning AI

• Develop and apply machine-learning and statistical approaches to protein structure, phenotypic, and other multimodal biological datasets.
• Curate, harmonize, and quality-control structured and unstructured data from internal and external sources.
• Build reproducible computational workflows for feature generation, model training, validation, and performance evaluation.
• Integrate protein structural representations with phenotypic and other biological data to generate testable hypotheses and prioritize follow-up analyses.
• Implement clear, maintainable analysis code and contribute to shared repositories and technical documentation.
• Communicate methods, findings, and recommendations clearly to technical and non-technical stakeholders.

Machine Learning, Artificial Intelligence (AI), Training Data Sets, Machine Learning, Unstructured Data, Quality Control, Structured Data, Performance Reviews, Performance Analysis, Model Validation, * Advanced degree (M.S. or Ph.D.) in computational biology, bioinformatics, computational chemistry, biophysics, or a related field.

• Hands-on experience applying machine learning to biological, chemical, or biomedical data.
• Experience working with protein structure data and/or structure-derived features in a research or drug discovery setting.
• Experience integrating or modeling phenotypic and multimodal datasets.
• Strong Python programming skills and experience with scientific computing and machine-learning libraries.
• Ability to independently execute defined project work and deliver high-quality outputs on an agreed timeline.