Senior Scientist, Computational Signal Processing

The Company

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 19 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.

• 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.

• 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 (Num Py, Sci Py, 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.

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

Flagship Pioneering invents and builds platform companies, each with the potential for multiple products that transform human health, sustainability and beyond. Since its launch in 2000, Flagship has originated more than 100 companies. Many of these companies have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture.

Flagship has been recognized twice on FORTUNE’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies and has been twice named to Fast Company’s annual list of the World’s Most Innovative Companies. Learn more about Flagship at

At Flagship, we accept impossible missions to enable bigger leaps. Our core values guide us through uncertainty and toward lasting impact.

All qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.

We recognize that great candidates often bring unique strengths without fulfilling every qualification
. If you have some of the experience listed above but not all, please apply anyway. We are…