Senior Director, Head of Computational Sciences

Flagship Pioneering•Cambridge, MA

About The Position

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. We are looking for a visionary, hands-on computational leader to build-out and lead Tilde's computational sciences. This person will own the algorithms, models, and data infrastructure that sit at the heart of our nanopore-based protein reading platform — from raw signal processing through to protein identification and quantification. The role is cross-functional by design. You will be embedded in the science, working directly with nanopore scientists, protein engineers, and the technology development team to turn experimental data into platform insight. At the same time, you will be building a team and shaping a longer-term computational roadmap. The right candidate has strong technical depth in machine learning and computational biology, has led teams before, and is comfortable operating in an environment where the science is still being defined.

Requirements

PhD in Computational Biology, Bioinformatics, Computer Science, Machine Learning, or a related field.
10+ years of experience in computational biology or a closely related area, with at least 4 years leading a team.
Track record of building and developing strong computational teams across different organizations.
Strong hands-on ML and programming skills, with fluency in modern data science tooling.
Experience with cloud environments (e.g., AWS, GCP) and building scalable data infrastructure.
Clear communicator — able to make complex computational work legible to experimental scientists and non-technical stakeholders alike.
Comfortable with ambiguity; able to make good decisions and keep teams moving when the problem is still being defined.

Nice To Haves

Experience with time-series signal analysis from sequencing, electrophysiology, or related sensing platforms.
Background in proteomics, single-molecule biophysics, or life science platform technologies.
Familiarity with protein structure, function, or engineering.
Experience with NGS data analysis and bioinformatics tool development.
Prior experience at a venture-backed biotech or life science tools company.
History of contributing to IP and scientific publications.

Responsibilities

Set the computational sciences strategy and roadmap, working with the leadership team to align priorities with where the platform needs to go.
Build the computational sciences team — recruiting, mentoring, and creating an environment where scientists do their best work and remain current on latest developments in their field.
Lead development of algorithms and models for processing, decoding, and interpreting signals from Tilde's nanopore-based protein reading platform.
Work closely with nanopore scientists and hardware engineers to advance a fast-evolving analytical framework.
Design and implement ML pipelines for protein identification, classification, and quantification, drawing on multi-modal datasets spanning proteomic, genomic, and platform-generated data.
Establish data management practices, versioning standards, and analytical SOPs that support reproducible, scalable science, including creating and maintenance of cloud infrastructure (e.g., AWS) that can handle platform-scale data generation.
Partner with research, molecular engineering, data science, and technology development — making sure computational capabilities stay integrated with what the experimental teams need.
Work with program leads on data generation strategies, experimental designs, and analysis frameworks.
Work with external collaborators or consultants, as needed, to accelerate our research productivity.
Identify and protect novel computational methods as part of Tilde's IP strategy.
Communicate technical progress clearly to leadership and, where relevant, to external partners and investors.