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
- Solid 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