Thesis Work, 30/60 Credits - Advancing AI-Driven Mechanism-of-Action Prediction from Cell Painting Images: Expanding the DeepPheno Platform
Core
Master's thesis project developing DeepPheno, an AI platform that predicts the mechanism of action of compounds from Cell Painting images to accelerate drug discovery.
Role type
Master's thesis researcher (AI/ML for drug discovery)
Builds
DeepPheno platform (AI models for MoA prediction)
Domain
Biopharmaceuticals / Drug Discovery / Computer Vision
Deliverable
production ML models
Required skills
Python programming, deep learning frameworks (PyTorch), image analysis, machine learning, biological data integration
Preferred skills
computer vision, self-supervised learning, multimodal AI, microscopy experience
Technologies
Python, PyTorch, Cell Painting images
Responsibilities
Evaluate modern AI models on larger datasets, integrate gene-expression and chemical data, improve model explainability, assess platform performance on unseen compounds, improve platform usability and documentation
Seniority
Master's student (Thesis Worker)
