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Scientist, Computational Sensing

Flagship Pioneering, Inc.·US·Cambridge, MA USA·mid
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About Tilde (FL110) Tilde Bio, Inc. (FL110) is building a next-generation biological sensing platform at the intersection of synthetic biology, protein engineering, nanopore biophysics, electrophysiology, signal processing, and machine learning. Our goal is to create programmable biological measurement systems capable of extracting rich molecular information from single-molecule interactions. We believe nanopores generate a high-dimensional measurement of molecular identity and behavior that remains largely untapped. Unlocking that information requires new computational approaches — ones that don't yet exist — built by people who are comfortable working at the edge of what's known. At Tilde, you will work alongside scientists and engineers from diverse disciplines to help define how a new generation of biological sensing systems extract meaning from the physical world. Tilde is backed by Flagship Pioneering, which brings the long-term vision and resources needed to build platforms that don't fit neatly into existing categories. Position Overview We are looking for a Bioinformatics Scientist to join our Computational Team to help build the analytical foundation that connects nanopore measurements to biological understanding. This role sits at the intersection of biology, physics, signal processing, and machine learning — you will work directly with experimental scientists and engineers to develop methods that transform complex biological measurements into actionable scientific insight. This role requires creating and implementing standard pipeline, and goes beyond them. Here, you will build fundamental approaches to understanding and processing electronic data into an interpretable format and create methods to transform that data into actionable sequencing outputs. The problems are open-ended, and many of the analytical frameworks don't exist yet. The right person enjoys working with noisy experimental data, building quantitative models from first principles, and col

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