Senior Scientist, Computational Signal Processing

Flagship Pioneering, Inc.•Cambridge, MA

35d•$115,000 - $209,000•Onsite

About The Position

Flagship Labs 119 Inc. (FL119) is an early-stage technology company pioneering a new frontier at the intersection of neuroscience and computation. We are developing next generation neuroimaging technologies to decipher the neural code and transform how intelligent systems are built. We believe that the future of artificial intelligence demands a fundamental rethinking of today's paradigms. Our mission is bold and urgent: to build a future where naturalistic, robust intelligence can emerge and operate sustainably at scale. FL119 is backed by Flagship Pioneering, which brings the courage, long-term vision, and resources needed to realize unreasonable results. At FL119, we are uniquely cross functional and collaborative. Our teams thrive in unstructured and creative environments. All voices are heard because we know that experience comes in many forms, skills are transferable, and passion goes a long way. FL119 is seeking a creative and talented Senior Computational Scientist, Signal Processing to join our team. Leveling is flexible based on experience. This role will focus on building data pipelines by applying signal processing and machine learning methods to large datasets generated by our neuroimaging platform. The role is based in Cambridge, Massachusetts, with a preference for on-site engagement.

Requirements

MSc or PhD in Computational Neuroscience, Computer Science, AI/ML, or a related field.
2+ years of full-time industry or postdoctoral experience (5+ years for MSc).
Experience developing signal processing and machine learning algorithms for time-series data (electrophysiological, neuro, audio, sequencing, etc.), statistical learning, and algorithm design.
Proficiency in Python and scientific computing libraries (NumPy, SciPy, Pandas, PyTorch or Tensorflow), and C/C++ for algorithm development and data analysis.
Comfort in high-ambiguity R&D environments and experience prototyping algorithms from scratch.
Passion for working at the intersection of AI and experimental biology.

Nice To Haves

Previous experience with processing and analyzing electrophysiology data.
Contributed to open-source data projects in biology/chemistry.

Responsibilities

Spearhead the design and development of signal processing pipeline for high frequency (kHz), noisy, spatiotemporal signal data.
Implementation of ML techniques for extracting quantitative parameters and functional relationships from signals to uncover transferable representations of cognition.
Deployment of tools and scripts for managing and analyzing large experimental datasets.
Shape the technical roadmap and lead the design of pivotal experiments.