Director Machine Learning Virtual Cell Initiative
Independent nonprofit AI-and-biology research institute developing biomedical AI models, data resources, and research tools.
About Arc Institute
Arc Institute is a Palo Alto-based nonprofit research organization founded in 2021. It supports long-term biomedical research and develops experimental and computational technologies, including virtual-cell models and open data resources, in partnership with Stanford, UC Berkeley, and UCSF.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
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.
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
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
Benefits
- Annual discretionary bonus
