🛠 Tech Stack

💼 About This Role

You'll develop machine learning models for single-cell and multiomic data to drive therapeutic discovery. You'll work in interdisciplinary teams alongside wet-lab scientists, translating biological questions into well-posed modelling problems.

🎯 What You'll Do

• Design and implement ML models for single-cell multiomic data
• Develop representation learning and probabilistic approaches for cellular state
• Contribute to the team's research roadmap on cellular modelling
• Work with experimental teams to interpret model outputs biologically

📋 Requirements

• PhD in machine learning, computational biology, statistics or related field
• Hands-on experience building ML models for biological data
• Strong foundations in probabilistic modelling or representation learning
• Python fluency with PyTorch or JAX

✨ Nice to Have

• Development of widely-adopted tools in single-cell ML ecosystem
• High-impact publications at ML and biology intersection
• Experience with perturbational datasets like Perturb-seq

🎁 Benefits & Perks

• 🏖️ Flexible working
• 🧬 Cutting-edge wet and dry labs in central London
• 🏥 Health insurance
• 📚 Learning and development budget
• 🚆 Commuter benefits

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter screen· 30 min
2. 2Technical interview· 60 min
3. 3On-site interviews· half day