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1 week ago
We are seeking a seasoned expert to lead the development of cutting-edge machine learning models for protein–ligand structure prediction, de novo molecular generation, and multi-objective optimization.
This role involves partnering with our Ligand Design & Pose Prediction Lead to integrate chemical and biological expertise into the model pipeline, ensuring that our AI agents produce compounds that are potent, novel, and biologically relevant.
- Develop innovative deep learning architectures for pocket-conditioned molecular generation, protein–ligand pose prediction, and multi-objective reinforcement learning.
- Tune AlphaFold/OpenFold and related structure models for project-specific targets.
- Integrate multi-modal biological context into generative and scoring models.
- Develop and maintain scoring functions for binding affinity, selectivity, ADMET, and synthetic accessibility.
Required Qualifications:
- PhD or MSc in Computer Science, Machine Learning, Computational Chemistry, Bioinformatics, or related field.
- 2+ years of hands-on experience in deep learning model development, preferably in a scientific or molecular domain.
- Strong expertise in generative modeling, 3D geometric deep learning, and reinforcement learning.
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