onsite
Machine Learning Research Scientist/Senior Machine Learning Research Scientist, Structure and Simulation AI for Drug
ML Engineer
Lead cutting‑edge research in AI for drug discovery, developing diffusion and geometric deep learning models on the Amber CHARMM platform to accelerate structure and simulation studies.
About the role
Key Responsibilities
- Design, implement, and evaluate diffusion and geometric deep learning algorithms for protein structure prediction and molecular simulation.
- Integrate advanced models with the Amber CHARMM software suite to generate high‑fidelity molecular dynamics data.
- Collaborate with computational chemists and data scientists to translate research findings into scalable, production‑ready pipelines.
- Publish results in top-tier conferences and journals, and present at internal and external meetings.
- Mentor junior researchers and contribute to the continuous improvement of research workflows.
Requirements
- Ph.D. or equivalent experience in Machine Learning, Computational Chemistry, or related field.
- Proven expertise in deep learning frameworks (PyTorch, TensorFlow) and experience with diffusion or geometric deep learning.
- Strong programming skills in Python and familiarity with Amber CHARMM or similar molecular dynamics packages.
- Excellent analytical, problem‑solving, and communication skills.
- Track record of publishing in high‑impact venues and contributing to open‑source projects is a plus.
Skills
machine learningdeep learning