Director Machine Learning Virtual Cell Initiative

You will lead a machine learning group developing foundation models and agentic frameworks for perturbative gene-expression modeling. You will partner with wet-lab scientists in an active learning loop, integrate genomic and omics data, pioneer new approaches, mentor researchers, recruit talent, and publish scientific breakthroughs.

Responsibilities

• Build and lead a team of machine learning research scientists and engineers
• Develop a foundation model and agentic framework for cellular responses to perturbations
• Work with wet-lab scientists to develop diverse single-cell training data
• Integrate genomics, functional track, and omics data beyond scRNA-seq and Perturb-seq
• Pioneer new machine learning architectures and approaches
• Build a virtual cell model for biologists
• Mentor and train scientists
• Recruit scientific and engineering talent

Requirements

• PhD in Computational Biology, Bioinformatics, Machine Learning, or a related field
• At least 5 years of machine learning experience
• Experience with PyTorch, TensorFlow, JAX, or similar frameworks
• Experience leading research teams in a fast-paced multidisciplinary environment
• Experience with or strong interest in biology
• Ability to communicate and collaborate with biologists and machine learning engineers
• Excellent written and verbal communication skills
• Strong record of presentations and publications

Benefits

• Annual discretionary bonus