Summer Internship: Machine Learning/deep Learning, Global Digital Health Intern (hybrid - San Carlos, Ca)
Beonemedicines
San Carlos, CA, USA
Masters: $30ph usd; phd: $35ph usd; not specified
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Machine learning/deep learning models
Python programming skills
Ml/dl frameworks (pytorch, tensorflow, jax)
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BeOne Medicines is offering a Summer Internship in Machine Learning/Deep Learning, focusing on Hematology and Oncology, for candidates currently enrolled in a relevant MS/PhD program. The hybrid role requires a strong foundation in programming and machine learning, with an emphasis on collaboration and innovation in the fight against cancer.
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Job Summary
This is a high-ownership internship for a candidate who wants to do meaningful technical work at the intersection of AI and disease-area strategy.
The intern will work directly with our Global Digital Health leadership and scientific leaders and partner with cross-functional stakeholders to frame important scientific or clinical questions.
This is a greenfield opportunity to help shape how advanced AI methods can support decision-making in a clinically important area.
Matching Summary
Match Score: 75
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BeOne Medicines is offering a Summer Internship in Machine Learning/Deep Learning, focusing on Hematology and Oncology, for candidates currently enrolled in a relevant MS/PhD program. The hybrid role requires a strong foundation in programming and machine learning, with an emphasis on collaboration and innovation in the fight against cancer.
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Salary
Masters: $30/hour USD; PhD: $35/hour USD; Not specified
Skills & Requirements
Must-have
Machine learning/deep learning models
Python programming skills
ML/DL frameworks (PyTorch, TensorFlow, JAX)
Real-world dataset model training
Translate scientific questions to modeling problems
Nice-to-have
Publication experience
Research experience in AI/ML
Biomedical/clinical dataset experience
Interest in oncology/healthcare AI
Key Requirements
MS/PhD program enrollment
Computer Science, Statistics, Biomedical Informatics, Computational Biology, or related quantitative field