Postdoctoral Scientist – AI & Machine Learning for Predictive Drug Absorption
Tasks
- Analyze large heterogeneous experimental biopharmaceutics and clinical pharmacokinetic datasets
- Build end to end machine learning pipelines for data ingestion feature engineering model training validation
- Communicate results via technical reports presentations and peer reviewed publications
- Contribute to AI enabled predictive platform development
- Design train evaluate machine learning models for oral drug absorption
- Develop compare tree based neural network surrogate model probabilistic approaches
- Develop explainable AI and interpretable modeling approaches
- Quantify model robustness generalizability and uncertainty
- Translate model outputs into actionable insights for drug development teams
Perks/Benefits
- 401k
- Dental insurance
- Health insurance
- Paid Holidays
- Paid caregiver/parental leave
- Paid medical leave
- Paid vacation
- Personal days
- Relocation assistance
- Travel reimbursement
- Vision insurance
Skills/Tech-stack
Artificial Intelligence | Data Ingestion | Explainable AI | Feature Engineering | Machine Learning | Mechanistic Learning | Model Evaluation | Model Interpretability | Neural Networks | Pharmacokinetic modeling | Physics-informed learning | Physiologically Based Biopharmaceutics Modeling | Physiologically Based Pharmacokinetic | Physiologically Based Pharmacokinetic Modeling | Probabilistic Models | PyTorch | Python | R | Scikit-learn | Surrogate modeling | TensorFlow | Tree-based Models | Uncertainty Quantification
Education
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