Director, Machine Learning, Alzheimer's Disease Initiative

Arc Institute is seeking a scientific leader to establish a new team within its Computational Technology Center as the Director, Machine Learning for the Alzheimer's Disease Initiative (ADI).

The Alzheimer's Disease Initiative focuses on high-throughput interrogation of neurodegeneration and Alzheimer's disease mechanisms using advanced gene editing and functional genomics approaches. As the Machine Learning Research Lead, ADI, you will spearhead the development of sophisticated machine learning foundation models to capture cell states and infer gene regulatory networks and causal relationships to predict therapeutic interventions.

Responsibilities:

• Attract, build, and lead a team of exceptional machine learning research scientists dedicated to developing foundation models for cellular systems in Alzheimer's disease
• Develop and execute on a roadmap of interpretable machine learning approaches to understand disease mechanisms, with emphasis on variational inference, causal modeling, as well as modern transformer- and diffusion-based architectures
• Work closely with experimentalists on brain organoid/spheroid cellular models as well as in vivo models, working with scRNA-seq, Perturb-seq, and other datasets to unravel causal gene pathways relevant to Alzheimer’s disease
• Develop predictive modeling approaches to identify how perturbations can move cell states from high-risk Alzheimer’s profiles back to healthy/low-risk states
• Collaborate closely with experimental biologists to ensure ML models are grounded in disease biology and can feedback into future experimental strategies
• Foster collaborations with external partners in the computational biology and neuroscience communities
• Publish high-impact research through preprints, journal publications, open-source code, and presentations at leading conferences

Requirements:

• PhD in Computational Biology, Bioinformatics, Machine Learning, Computer Science, or related quantitative field
• 7+ years of relevant experience with a minimum of 3 years of people management experience
• Strong research background with experience in academic settings (university, research institute) and/or biotech/pharmaceutical industry with a focus on scientific innovation
• Proven expertise in machine learning applications to biological datasets, with specific experience in single-cell profiling data and foundation model development
• Deep experience with interpretable machine learning approaches for biological systems (e.g., variational inference methods)
• Advanced technical skills in machine learning frameworks, particularly PyTorch, and ideally experience with model training at scale
• Publications in top-tier journals in computational biology and machine learning
• Excellent communication skills with the ability to present complex machine learning concepts to both computational and biological audiences
• Proven ability to remain technically hands-on while providing effective team leadership, mentorship, and management
• Background in neurodegeneration research, including familiarity with Alzheimer's disease datasets, pathways, networks, disease mechanisms, and eQTL analysis, is a plus

The base salary range for this position is $380,000-$420,000.