Postdoctoral Fellow – AI/ML Enabled Bioprocess Modeling and Control

Tasks

• Apply machine learning and deep learning for clustering and performance prediction
• Collaborate with cross functional teams and mentor junior scientists
• Communicate results through presentations and publications
• Deploy models prospectively for new development programs
• Design and conduct shake flask ambr bench bioreactor experiments for data generation
• Develop hybrid mechanistic data driven models for mammalian cell culture processes
• Develop model predictive control framework for real time process control
• Explore agentic AI for model fitting and transfer learning with human in the loop
• Extend mechanistic bioprocess models with physiological functions
• Integrate transcriptomic and omics data for clone specific prediction
• Maintain electronic laboratory notebooks and technical reports
• Perform in silico sensitivity and scenario analysis
• Validate models and control strategies using historical and new datasets

Perks/Benefits

• Relocation support

Skills/Tech-stack

Bioprocess Modeling | Cell Culture | Classification | Clustering | Data integration | Deep learning | Genome-scale modeling | Human-in-the-loop | Hybrid Modeling | Julia | Kinetic modeling | MATLAB | Machine Learning | Mammalian cell culture | Mathematical Modeling | Model Validation | Model-Predictive Control | Multi-task Learning | Omics Data | Omics data integration | Optimization | Predictive control | Python | Reaction kinetics | Regression | Scale modeling | Scenario Analysis | Sensitivity Analysis | The Loop | Transcriptomics | Transfer Learning