Set scientific direction for deep learning on genomic data in Toronto, with independence spanning architectures, pre-training, and biological interpretation. Deep Genomics seeks senior or staff-level research scope for biological foundation models. The scientist will develop methods that learn patterns from genome and other -omics data at large scale. Success depends on connecting machine learning research with genome biology, meaningful questions, and genetic medicine discovery.

Key Responsibilities: Set direction for large-scale genomic model research Create deep learning architectures for genome data Develop new model pre-training approaches Judge the significance of biological findings Tie model outputs to real drug discovery decisions Requirements: Deep expertise in machine learning research Robust genome biology knowledge Ability to work independently and set direction Evidence through published research or open projects Experience connecting models with biological questions Shape independent genomics research through deep learning architectures, pre-training methods, and biology-driven model evaluation at Deep Genomics.

📌 Staff Deep Learning Scientist Genomics (Toronto)
🏢 present of AI
📍 Toronto