ABOUT FLAGSHIP PIONEERING

Flagship Pioneering is a platform innovation company that conceives, creates, resources, and develops first-in-category life sciences and technology companies. Since its founding in 2000, Flagship has originated over 100 scientific ventures and has deployed over $3 billion in capital toward the development of transformative life science businesses. Flagship's current portfolio of more than 35 companies includes Moderna, Generate Biomedicines, Sail Biomedicines, iris labs, and Extuitive.

ABOUT FL127

FL127 is a privately held, early-stage company operating within the Flagship Pioneering ecosystem. The company is developing a first-in-category platform anchored in novel device technology. FL127 is building its scientific and technical foundation through a hypothesis-driven experimental program. We are assembling a lean team of scientists and engineers who work at the intersection of hardware, software, and physiology, and who want to build in an era when AI agents are first-class members of the team.

THE ROLE

FL127 is seeking a scientist to help connect the physiological signals our platform measures to what they indicate about a person. You will ground each signal in physiology, help design the human studies that test what it reflects, and build models that relate our measurements to reference measures and outcomes in small human cohorts.

Our imaging and signal-extraction team produces the measurements. Your work starts from those outputs. You will co-design human studies with that team so a single study informs both measurement quality and interpretation.

FL127 is an AI-native company. Team members direct AI agents in their daily work for literature synthesis, study design, data analysis, and code. We are looking for someone who wants to work this way.

KEY RESPONSIBILITIES

Ground each measured signal in physiology: what it reflects, what confounds it, and which physiological states it may indicate
Work with the product and market team to decide which applications to study first, weighing scientific plausibility, study cost, and user value
Co-design human studies with the imaging team, including endpoints, reference measurements, and protocols
Build and evaluate models that relate our measurements to reference measures and outcomes on small cohorts, with attention to confounders, leakage, demographic stratification, and sample size
Set the evidence bar a finding must meet before it shapes the product, and report what the data supports and where it falls short
Review extracted signals for physiological plausibility and suggest improvements to the measurement pipeline

REQUIRED QUALIFICATIONS

PhD in biomedical engineering, physiology, bioengineering, biophotonics, or a related field, or an MD/PhD, with substantial applied machine learning experience
Deep knowledge of human physiology in an area such as microcirculation, hemodynamics, tissue optics, skin biology, or cardiorespiratory physiology
Experience taking a measurement or digital biomarker through human studies, including endpoint selection, reference measurements, IRB-governed protocols, and agreement analysis
Statistical modeling on small human datasets, including within-subject and longitudinal designs
Proficiency in Python and the modern ML stack, and comfort working inside an existing research codebase
Enough imaging and signal-processing background to reason about how calibration, registration, and sampling affect a derived measurement
Ability to work independently in an early-stage, ambiguous environment and make decisions with incomplete data

PREFERRED QUALIFICATIONS

Published or applied work in remote physiological sensing, digital biomarkers, or wearable or contactless measurement
Experience turning research results into a product feature, ideally at a consumer device company
Familiarity with skin optics models (Monte Carlo simulation, diffusion theory, chromophore decomposition)
Experience modeling individual baselines and change over time
Experience in a venture-backed startup or early-stage research environment