Head of Computational Sciences & ML Platforms

Flagship Pioneering, Inc.; Cambridge (MA); On-site; USD 223,000 - 294,000; Full time

Job summary

Tilde Bio, Inc. is seeking 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, embedded with scientists and engineers to turn experimental data into platform insight.

Qualifications

• PhD in a relevant field with 10 years in computational biology or related area, incl. 4+ years leading a team.
• Track record of building and developing strong computational teams across organizations.
• Strong hands-on ML and programming skills with fluency in modern data science tooling.

Responsibilities

• Lead development of algorithms and models for processing, decoding, and interpreting signals from Tilde’s nanopore-based protein reading platform.
• Work with nanopore scientists and hardware engineers to advance the analytical framework.
• Design and implement ML pipelines for protein identification and quantification using multi-modal data.
• Establish data management, versioning standards, and SOPs, incl. cloud infrastructure (e.g., AWS) for scalable data generation.
• Partner with research teams to align computational strategy with experimental needs and communicate progress to leadership.

Skills

Machine Learning

Computational Biology

Programming

Cloud AWS/GCP

Leadership

Education

PhD in Computational Biology

Tools

Python

TensorFlow

PyTorch

AWS

GCP

Job description

Tilde Bio, Inc. is seeking 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, embedded with scientists and engineers to turn experimental data into platform insight.