remote
AI Drug Discovery Scientist
Software Engineer
Lead the design of next‑generation oncology therapeutics by applying generative machine learning to small‑molecule and beyond‑Rule‑of‑5 drug discovery, driving end‑to‑end pipeline acceleration from target identification to clinic‑ready candidates.
About the role
Key Responsibilities
- Develop and refine generative ML models to propose novel small‑molecule and bRo5 candidates for oncology targets.
- Collaborate with medicinal chemists and biologists to translate computational predictions into experimental designs.
- Analyze high‑throughput screening data, integrate multi‑omics datasets, and generate actionable insights for lead optimization.
- Iterate model architectures, evaluate performance metrics, and maintain reproducible research pipelines.
- Communicate findings to cross‑functional teams, influencing strategy and prioritization of drug candidates.
Requirements
- PhD or MS in Computational Chemistry, Bioinformatics, or related field with strong ML background.
- Proficiency in Python, deep learning frameworks (PyTorch/TensorFlow), and cheminformatics libraries.
- Experience with generative models (e.g., VAEs, GANs) applied to drug design.
- Solid understanding of oncology biology and drug‑discovery workflows.
- Excellent problem‑solving skills and ability to work in a fast‑paced, collaborative environment.
Skills
pythonmachine learning