Чётко описанная стажировка в крупной биофармацевтической компании даёт практический опыт в моделировании процессов и data science, а также наставничество. Однако обязательная работа в офисе шесть месяцев и строгие требования к разрешению на работу подходят не всем.
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Ограничения по работеПонятные задачиПерспективная отрасльНаставничествоОриентир по оплате
Оценка от Hirify AI
Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
2027 Spring Co-op Data Science & Digital Transformation (Bioprocess Modeling): Developing hybrid modeling and simulation applications to improve understanding, monitoring, and control of cell culture manufacturing processes with an accent on process data analysis, digital twins, and process innovation. Focus on identifying atypical results, testing simulation platforms and user interfaces, and collaborating with scientists and engineers on robust bioprocess solutions.
Location: Framingham, Massachusetts, United States; must relocate to the office and work onsite 40 hours per week, Monday through Friday, for the six-month co-op.
Salary: $35–$57 per hour
Company
hirify.global is an R&D-driven, AI-powered biopharmaceutical company developing medicines and vaccines to improve patient outcomes.
What you will do
Evaluate and develop hybrid modeling techniques for cell culture processes.
Use simulations and process data to identify atypical results.
Test simulation platform and user interface capabilities for new use cases.
Collaborate with scientists and engineers across research and manufacturing.
Create presentations, user guides, reports, and other documentation.
Requirements
Currently enrolled in an accredited college or university throughout the co-op in a bachelor's, master's, or PhD program in chemical engineering, biological engineering, biochemistry, computer science, or a related field.
Permanently authorized to work in the United States without current or future employment visa sponsorship.
Able to relocate to the Framingham office and work onsite full time for the entire six-month program.
Knowledge of computer programming concepts; Python is preferred.
Understanding of basic chemical reaction mechanisms, empirical equations, cell growth, and metabolism.
Nice to have
Experience with scientific literature searches.
Experience with mechanistic, statistical, or machine learning techniques.
Culture & Benefits
Mentoring and guidance from experienced leaders.
Collaborative work with scientists and engineers on real healthcare projects.
Access to digital innovation, current tools, apprenticeships, and continuous learning opportunities.
Opportunity to contribute to next-generation manufacturing and analytical processes.