Grad Co-op – Computational Safety Modeling for Small Molecules

This is a fully remote position, open to applicants in United States.

📋 Description

• Enhance Amgen’s computational toolkit for evaluating the safety of small molecule drug candidates and potentially other modalities.

• Collaborate with computational scientists and nonclinical safety professionals to make early drug-discovery safety predictions.

• Identify, curate, and analyze both external and internal data, such as chemical structures, assay results, and exposure information.

• Develop and assess structural alerts, analogue-based read-across, machine learning techniques, and models that integrate experimental findings with other safety data.

• Assess model performance on relevant compounds.

• Document the context of use, uncertainties, applicability, and limitations.

• Work alongside computational scientists, medicinal chemists, and toxicologists to inform compound prioritization and subsequent experiments.

• Present findings and provide reproducible analyses, documented model prototypes, and development suggestions.

• Establish mechanisms for retraining as new data becomes available over time.

⛳️ Requirements

• Must be available to work on a part-time basis.

• Expected to maintain enrollment in an accredited college or university post-internship program/co-op.

• Student must reside in the United States for the duration of the internship program.

• Must be 18 years or older.

• Must have graduated with a bachelor’s degree from an accredited college or university.

• Currently enrolled in an MBA, Master’s, PharmD, or Ph.D. program at an accredited institution.

• Completion of the first year of the relevant graduate program is required before the internship commences.

• Must be pursuing a graduate degree in cheminformatics, bioinformatics, computational chemistry or biology, data science, statistics, toxicology, or a related field.

• Experience in utilizing Python for scientific data analysis.

• Familiarity with statistical modeling and machine learning, including principles of model evaluation.

• Ability to clearly communicate technical findings and collaborate with scientists from diverse disciplines.

• Experience in cheminformatics, predictive toxicology, or in vitro assay data analysis.

• Familiarity with small molecule drug discovery or nonclinical safety assessment.

• Experience in integrating data from multiple sources and documenting reproducible computational workflows.

• Familiarity with version control and collaborative software development practices.

• Candidates must be authorized to work in the U.S. throughout the duration of this program.

🏝️ Benefits

• Competitive benefits package.

• Collaborative work culture.

• Support for professional and personal growth and well-being.

• Opportunities for networking with colleagues.

• Access to executive and social networking events.

• Participation in community volunteer projects.

• An inclusive culture that values diverse thoughts and experiences.

• Reasonable accommodations for individuals with disabilities.