Senior/Principal Machine Learning Scientist, Structure and Simulation (AI for Drug Discovery)
Core
Developing unified machine learning models to transform drug discovery from a balkanized process into a coherent, lab-in-the-loop system for large molecule discovery.
Role type
Senior/Principal Machine Learning Scientist (AI for Drug Discovery)
Builds
Unified machine learning models for structure-based hit finding and ligand-based lead optimization
Domain
Biopharmaceuticals / Computational Chemistry / Machine Learning
Deliverable
production ML models
Required skills
Python, deep learning (PyTorch, TensorFlow, JAX), reinforcement learning, sampling, multimodal representation learning, designing ML systems for molecules and biological sequences
Preferred skills
None stated
Technologies
PyTorch, TensorFlow, JAX
Responsibilities
Develop novel machine learning methods to answer challenging research questions in large molecule drug discovery; Work with biological and chemical data from heterogeneous sources; Contribute to/Lead an initiative to consolidate projects in machine learning theory into a single coherent model for lab-in-the-loop drug discovery
Seniority
Senior (BS+7 to PhD+2 years) / Principal (BS+10 to PhD+5 years), hands-on IC with research leadership