13 дней назад
2027 Spring Co-op Machine Learning AI (Biotech)
47 - 60$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
2027 Spring Co-op Machine Learning AI (Biotech): Developing and validating AI/ML models for biologics pharmacology dynamics by integrating structural, preclinical, and clinical data with an accent on drug discovery, pharmacology, and data-driven decision making. Focus on designing and training biology- and pharmacology-based models, interpreting complex datasets, and supporting early drug development decisions.
Location: Cambridge, MA; must relocate to the office and work onsite 40 hours per week, Monday to Friday, for the full six-month co-op
Salary: $47–$60 per hour
Company
is an R&D-driven biopharma company developing medicines and vaccines through science, healthcare innovation, and AI-powered research.
What you will do
- Implement, develop, and validate data-based AI/ML models for drug discovery and development.
- Predict pharmacology dynamics of biologics by integrating structural, preclinical, and clinical data.
- Analyze and interpret preclinical and clinical datasets.
- Design and train biology- and pharmacology-based models.
- Support early drug development decisions across therapeutic areas and research platforms.
Requirements
- Currently enrolled in a Master's or PhD STEM program and enrolled throughout the co-op.
- Permanently authorized to work in the U.S. without current or future employment visa sponsorship.
- Must be able to relocate to Cambridge and work onsite full time for the entire co-op.
- Experience with Python and relevant libraries.
- Experience with statistical or machine learning methods.
Nice to have
- Knowledge of drug discovery and development, especially biologics.
- Experience with large language models, deep learning, or time-series data modeling.
- Strong written, presentation, and verbal communication skills.
- Ability to work in a matrix and global environment.
Culture & Benefits
- Mentoring and guidance from experienced leaders.
- Access to current tools, digital innovation, and continuous learning.
- Opportunity to contribute to real healthcare and drug development projects.
- Supportive and collaborative working environment.
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