Principal Machine Learning Scientist, Drug Discovery Analytics
Redwood City, California, United States
USD 273K-321K Senior-level Full Time
Tasks
- Apply graph neural networks for molecular representation
- Build deep learning models for molecular representation
- Define machine learning strategies for early stage drug discovery
- Deploy models into scalable discovery workflows
- Develop generative chemistry models
- Develop predictive models for compound activity selectivity ADMETox and developability
- Develop predictive models for target engagement mechanism of action and phenotypic datasets
- Implement active learning frameworks for experimental design
- Integrate heterogeneous chemical biological and phenotypic datasets
- Partner with biologists to interpret experimental datasets and generate mechanistic hypotheses
- Partner with medicinal chemists to guide compound design and optimization
Perks/Benefits
- N/A
Skills/Tech-stack
Active Learning | Bioinformatics | Chemical informatics | Cloud Computing | Data integration | Deep learning | Generative Modeling | Graph Neural Networks | Machine Learning | Neural Networks | NumPy | Pandas | PyTorch | Python | Scikit-learn | TensorFlow
Education
Regions
Countries
States
Cities
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