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Data Scientist III - Bioprocess Digital Twin
Data Scientist
Lead the development of AI‑driven digital twins for bioreactor operations, applying Bayesian optimization and machine‑learning techniques to detect cell‑culture drift and improve process efficiency.
About the role
Key Responsibilities
- Design and implement digital twin models that simulate bioreactor behavior and cell‑culture dynamics.
- Apply Bayesian optimization and advanced machine‑learning algorithms to identify optimal operating conditions and detect drift in cell cultures.
- Integrate real‑time sensor data streams into predictive models and ensure robust data pipelines on cloud platforms.
- Collaborate with bioprocess engineers to translate model insights into actionable process improvements.
- Validate model performance through experimental runs and continuously refine algorithms for scalability.
Requirements
- Ph.D. or Master’s in Bioengineering, Computer Science, Data Science, or related field with 5+ years of experience in bioprocess analytics.
- Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, scikit‑learn) and experience with Bayesian optimization frameworks.
- Hands‑on experience building digital twins or process simulation models for bioreactors or similar systems.
- Strong background in cell‑culture data analysis, drift detection, and statistical modeling.
- Experience with cloud services (AWS, Azure) for data processing and model deployment.
Skills
pythonmachine learningaws