Intern, Molecular Modeling & Informatics at Alkermes in Waltham, MA

• Build and evaluate machine learning models using chemical structure and assay data, with an emphasis on regression and classification tasks relevant to drug discovery. 
• Apply modern cheminformatics and ML toolkits including ChemProp, scikit-learn, and RDKit to generate molecular representations and predictive models. 
• Characterize model performance using appropriate validation strategies, including assessment of experimental error, noise, and upper bounds on achievable performance. 
• Analyze internal assay datasets to understand data quality, variance, and implications for model reliability. 
• Use model outputs to help inform decisions around potentially relevant chemical space and compound prioritization. 
• Communicate results clearly through written summaries, figures, and presentations to technical stakeholders. 
• If suitable this position will also contribute to the development of reusable, well documented modeling components that can be integrated into existing internal platforms and workflows.

Basic Qualifications: 

• Enrollment in, or recent completion of, a degree program in computer science, data science, statistics, computational chemistry, cheminformatics, chemical engineering, or a related quantitative discipline.

Preferred Qualifications: 

• Fundamental understanding of machine learning concepts, including model training, validation, and evaluation. 
• Experience working with Python for data analysis or modeling. 
• Familiarity with structured scientific datasets and basic data cleaning / preprocessing. 
• Ability to reason about uncertainty, error, and limitations in data‑driven models. 
• Strong analytical thinking skills and attention to detail. 
• Ability to communicate technical ideas clearly in written and verbal form.
• Hands‑on experience building machine learning models using ChemProp, scikit‑learn, or similar frameworks.
• Experience using RDKit or related cheminformatics libraries for molecular featurization and analysis. 
• Strong Python coding skills, including experience writing modular, testable, and maintainable code.
• Experience developing reproducible modeling pipelines, including version control, parameter tracking, and evaluation workflows. 
• Familiarity with experimental assay data, experimental variability, or model error analysis in scientific or engineering contexts.
• Exposure to software engineering best practices such as unit testing, code reviews, and documentation. 
• Interest in applying machine learning to real‑world scientific decision making rather than purely theoretical modeling.

Working Conditions: 

• Office‑based role with day-to-day work onsite at 900 Winter Street in Waltham
• Standard office environment with extensive computer‑based work. 
• Regular interaction with scientists and technical staff within Research.
• Ability to sit for extended periods while working at a computer. 
• Ability to use standard office equipment (computer, keyboard, monitor). 
• No special physical demands beyond typical office work.

The hourly rate for this position ranges from $23/hr to $27/hr. Exact compensation may vary based on skills, training, knowledge, and experience. Additional details can be found on our careers website: www.alkermes.com/careers#working-here