Scientist, Computational Sensing

About the role

Flagship Pioneering, Inc. is seeking a Scientist, Computational Sensing to join their growing team in Cambridge, Massachusetts. This role centers on developing computational methods and predictive models that enable the detection, interpretation, and classification of biological signals through advanced sensing technologies. The Scientist will operate at the intersection of data science, molecular biology, and sensor engineering to support Flagship's portfolio of innovative life sciences ventures. You will contribute to building analytical frameworks that transform raw sensing data into meaningful biological insights, helping guide decision-making across multiple venture teams. The work involves close collaboration with experimentalists, engineers, and business stakeholders to ensure computational approaches are grounded in real-world biological questions. This position plays a critical role in accelerating the pace of discovery by bridging computational analysis with experimental validation in a fast-moving innovation environment.

Key facts

What you'll do

Design and implement computational pipelines for processing data from biological sensing platforms and laboratory instruments

Develop machine learning models to identify meaningful patterns in complex sensing datasets generated by Flagship ventures

Collaborate with experimental biologists and hardware engineers to define sensing requirements and validate computational predictions against ground truth

Build statistical frameworks for quantifying signal quality, sensitivity, and specificity across diverse sensing modalities and assay types

Create interactive visualization tools and dashboards that communicate sensing data findings to cross-functional research teams

Write production-quality code in Python or R to automate data analysis workflows and ensure full reproducibility of results

Perform exploratory data analysis on large-scale sensing datasets to uncover new biological relationships and potential biomarkers

Contribute to peer-reviewed publications and internal knowledge-sharing sessions that document methods, benchmarks, and analytical results

Optimize existing algorithms for speed, accuracy, and scalability as the volume and complexity of sensing data continues to grow

Participate in code reviews and provide mentorship to junior team members on best practices for computational research

Evaluate and compare different sensing technologies and computational approaches to recommend the best methods for specific biological applications

Requirements

PhD in computational biology, bioinformatics, computer science, or a closely related quantitative discipline

At least 3 years of postdoctoral or industry experience working with biological sensing, genomics, or high-throughput data

Strong proficiency in Python and hands-on experience with scientific computing libraries such as NumPy, pandas, and scikit-learn

Demonstrated track record of analyzing complex biological datasets using statistical methods, regression, and machine learning approaches

Experience with signal processing techniques applied to biological, chemical, or physical sensing data in a research setting

Familiarity with version control systems, particularly Git, for collaborative software development and code management

Ability to communicate technical findings clearly through written reports, presentations, and documentation for diverse audiences

Comfortable working in a fast-paced startup environment with shifting priorities, ambiguous problems, and tight timelines

Nice to have

Experience with deep learning frameworks such as TensorFlow or PyTorch for biological data analysis and pattern recognition

Background in microfluidics, lab-on-a-chip systems, or other microscale sensing technologies and their computational challenges

Prior experience working in a venture capital or innovation studio environment where research directly supports investment decisions

Knowledge of cloud computing platforms such as AWS or Google Cloud for large-scale data processing and storage

Familiarity with regulatory standards for biosensing devices and diagnostic tools in the United States market

Skills & tools

Python programming for data analysis, machine learning, and scientific computing applications

Statistical modeling and hypothesis testing frameworks for biological data interpretation

Biological signal processing and time-series analysis methods for sensor data

Data visualization libraries including matplotlib, seaborn, and plotly for exploratory and presentation graphics

SQL and database management for storing, querying, and organizing experimental results and metadata

Linux command-line environments and high-performance computing clusters for large-scale data processing

Git and collaborative software development workflows for research teams and version-controlled projects

Practical notes

This position is based in Cambridge, Massachusetts and requires on-site presence during standard business hours each week

Flagship Pioneering, Inc. provides a collaborative research environment with access to advanced laboratory and computing resources

The role reports to a senior computational lead within the sensing technology group and works across multiple teams

Candidates should expect to engage regularly with venture teams across Flagship's portfolio on analytical projects and method development