Industrial PhD student in Machine Learning and Drug Design in Molecular AI

Tasks

• Build physics informed machine learning models for binding affinity prediction
• Design generative models for chemically plausible compounds
• Develop precision ML AI models for rational small molecule drug design
• Integrate physics based features with deep learning methods
• Prioritize candidates from hit discovery through lead optimization

Perks/Benefits

• Interdisciplinary collaboration
• Research Affiliation
• Seminars

Skills/Tech-stack

Affinity prediction | Artificial Intelligence | Binding Affinity Prediction | Computational Chemistry | Computational Workflows | Deep learning | Diffusion Models | Generative Models | Graph Neural Networks | High Performance | High-Performance Computing | Machine Learning | Molecular Dynamics | Molecular Modeling | Molecular mechanics | Neural Networks | Performance Computing | Python | Quantum Mechanics | Transformers | Workflow automation