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.
Responsibilities
Develop and apply machine-learning and statistical approaches to protein structure and multimodal biological datasets.
Curate, harmonize, and quality-control structured and unstructured data from various sources.
Build reproducible computational workflows for feature generation and model evaluation.
Integrate protein structural representations with biological data to generate testable hypotheses.
Implement clear, maintainable analysis code and contribute to shared repositories.
Communicate methods and findings clearly to both technical and non-technical stakeholders.
Full Job Description
Key Responsibilities:
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.
Qualifications:
dvanced 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.
bility to independently execute defined project work and deliver high-quality outputs on an agreed timeline.
