Director, Machine Learning, Alzheimer's Disease Initiative
Core
Lead the development of sophisticated machine learning foundation models to capture cell states, infer gene regulatory networks, and predict therapeutic interventions for Alzheimer's disease.
Role type
Director, Machine Learning Research Lead (Scientific Leader)
Builds
Interpretable ML foundation models for cellular systems and causal gene pathway analysis
Domain
Computational Biology / Neuroscience / Alzheimer's Disease
Deliverable
production ML models
Required skills
Machine learning foundation models, variational inference, causal modeling, transformer architectures, diffusion models, single-cell profiling data analysis, PyTorch, team leadership, scientific publication
Preferred skills
Alzheimer's disease datasets, eQTL analysis, brain organoid/spheroid models, in vivo models
Technologies
PyTorch, transformer architectures, diffusion-based architectures
Responsibilities
Attract and lead a team of ML research scientists; develop interpretable ML approaches for disease mechanisms; collaborate with experimentalists on cellular and in vivo models; develop predictive modeling for cell state transitions; foster external collaborations; publish high-impact research
Seniority
Director, hands-on IC with people management
