FL127 | Cambridge, MA Scientist, Machine Learning (Human Physiology)

Flagship Pioneering, Inc.; Cambridge (MA); On-site; USD 136,000 - 212,000; Full time

Benefits offered by this job

Healthcare coverage

Retirement benefits

Annual incentive program

Comprehensive benefits

Job summary

FL127, part of the Flagship Pioneering ecosystem, seeks a Scientist, Machine Learning (Human Physiology) in Cambridge, MA to connect physiological signals our platform measures with outcomes in small human cohorts. You will co-design studies with the imaging team and build models linking measurements to reference measures.

We seek a PhD with deep physiology knowledge and strong Python/ML skills to work with AI agents in literature synthesis, study design, data analysis, and coding within an

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 areas 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.
• Imaging and signal-processing background to reason about calibration, registration, and sampling effects on derived measurements.
• Ability to work independently in an early-stage, ambiguous environment and make decisions with incomplete data.

Responsibilities

• Ground each measured signal in physiology and identify what it reflects and confounds.
• Collaborate with product/market teams to select applications to study first based on plausibility, cost, and value.
• Co-design human studies with imaging team, defining endpoints, reference measurements, and protocols.
• Build and evaluate models relating measurements to reference measures and outcomes in small cohorts, addressing confounders and demographic factors.
• Set the evidence bar for findings to influence products and report strengths/limitations of data.
• Review extracted signals for physiological plausibility and suggest improvements to the measurement pipeline.

Skills

Python

Machine learning

Statistics

Signal processing

Education

PhD in biomedical engineering or related field

Job description

Scientist, Machine Learning (Human Physiology)

Cambridge, MA USA

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

WHY FL127

• Work with human study data from your first weeks
• Shape which applications the company studies and builds first
• Join a small team where scientists and AI agents work side by side
• Draw on the scientific, operational, and capital resources of the Flagship Pioneering ecosystem

The salary range for this role is $136,000 - $211,750. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. FL127 currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on FL127's good faith estimate as of the date of publication and may be modified in the future.