(Senior) Scientist, Computational Neuroscience

Flagship Pioneering, Inc.•Cambridge, MA

6d•$132,000 - $259,000•Onsite

About The Position

Flagship Labs 119 Inc. (FL119) is an early-stage technology company focused on the intersection of neuroscience and computation, aiming to develop next-generation technologies for building intelligent systems. The company believes that the future of artificial intelligence requires a reevaluation of current paradigms and is dedicated to creating a future where naturalistic, robust intelligence can emerge and operate sustainably at scale. FL119 is supported by Flagship Pioneering, providing the necessary resources and long-term vision for ambitious goals. The company fosters a cross-functional, collaborative, and creative environment where diverse experiences and perspectives are valued. This specific role will concentrate on developing scalable computational pipelines for biophysical modeling and applying machine learning to extensive neural datasets.

Requirements

MSc or PhD in Computational Neuroscience, Physics, Applied Mathematics, Computer Science, AI/ML, or a related field.
2+ years of full-time industry or postdoctoral experience (5+ years for MSc).
Strong experience with computational modeling of neural systems.
Hands-on experience applying machine learning or statistical methods to complex time-series data.
Proficiency in Python and scientific computing libraries (e.g., NumPy, SciPy, Pandas).
Familiarity with ML frameworks such as PyTorch or TensorFlow.
Comfort working in high-ambiguity R&D environments and building novel methods from first principles.
Passion for working at the intersection of AI and experimental biology.

Responsibilities

Own the development of end-to-end computational pipelines for biophysical modeling of neurons and neural populations.
Implement machine learning and statistical inference methods to construct and analyze bio-realistic networks from neural recordings.
Actively shape the technical roadmap by proposing, prototyping, and evaluating modeling and inference approaches in close collaboration with the broader team.