Advanced degree (M.S. or Ph.D.) in computational biology, bioinformatics, or related field.
Hands-on experience with machine learning in biological or biomedical contexts.
Familiarity with protein structure data in research or drug discovery.
Experience with phenotypic and multimodal dataset integration.
Strong Python programming skills, particularly with scientific computing libraries.
Ability to work independently and deliver quality outputs on time.
Responsibilities
Develop machine-learning and statistical models for multimodal biological datasets.
Curate and ensure the quality of structured and unstructured data from various sources.
Build reproducible workflows for model training and performance evaluation.
Integrate protein structures with phenotypic data to form testable hypotheses.
Implement maintainable analysis code and contribute to documentation.
Communicate findings to both technical and non-technical audiences.
Benefits
Opportunity to work on cutting-edge research in computational biology.
Collaborative environment with interdisciplinary teams.
Access to state-of-the-art tools and technologies.
Professional development opportunities in data science and bioinformatics.
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.
