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HomeCompaniesInsitroSenior Scientist, Cardiac Modeling

Senior Scientist, Cardiac Modeling

Insitro · South San Francisco, CA · Hybrid · Active · $156,000–$166,000 / year · Ashby

Job facts

FieldValue
CompanyInsitro
TitleSenior Scientist, Cardiac Modeling
Normalized title-
Department / teamTherapeutic Areas / Therapeutic Areas, Metabolic Diseases
LocationSouth San Francisco, CA, United States
Work modelHybrid / Hybrid
Employment typeFull Time
Salary$156,000–$166,000 / year
Statusactive
ATS providerAshby
Posted / first seen / 2026-06-17
Changed / last seen2026-06-17 / 2026-06-19

Related slices

PageWhat it containsOpen
Company jobsActive postings from Insitro.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through Ashby.Open
Provider filtered searchThe same provider as a filtered job collection.Open
City jobsActive postings in South San Francisco.Open
Department jobsActive postings in Therapeutic Areas.Open
Work model jobsActive Hybrid postings.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyInsitro
Source917579bf-4831-4f84-894f-f8f55008e633
ATS providerAshby

Description

The Opportunity insitro is a physical AI company dedicated to unlocking causal human biology and accelerating the delivery of better medicines to patients. Our unique Virtual Human™ platform identifies novel, high-impact genetic intervention points, which our TherML™ platform translates into therapeutics—whether small molecules, biologics, or oligos. With multiple programs in metabolic disease and neuroscience advancing toward the clinic, and our first IND submission slated for the second half of this year, we are at a pivotal inflection point. We are seeking a Senior Scientist to join our cardiac disease biology team. In this role, you will own the development and application of iPSC-derived cardiomyocyte (iPSC-CM) models to study the genetic and molecular underpinnings of cardiovascular disease — working at the intersection of human stem cell biology, cardiac physiology, and scalable experimental platforms to generate the datasets that fuel our ML-driven drug discovery efforts. You will design and execute experiments, optimize differentiation and assay workflows, and partner closely with ML scientists, computational biologists, and chemists to connect cellular phenotypes to disease mechanisms and therapeutic targets. Based in South San Francisco, this position reports directly to Vice President, Cardiometabolic Disease - Translational Genetics and requires you to be onsite at our South San Francisco office 5 days per week . Responsibilities iPSC-CM Platform & Model Development Differentiation & QC: Lead the generation, characterization, and maintenance of iPSC lines and their differentiation into cardiomyocytes, with rigorous quality control at each stage of the pipeline 2D & 3D Formats: Design, implement, and optimize iPSC-CM assays in both 2D monolayer and 3D/engineered heart tissue (EHT) formats, with a focus on scalability and data quality Genetic Disease Models: Build and apply isogenic iPSC-CM disease models — including CRISPR-edited lines carrying disease-associated variants — to study cardiovascular pathophysiology Functional Assays & Disease Modeling Functional Readouts: Develop readouts of cardiomyocyte biology relevant to disease —contractility, electrophysiology, calcium handling, stress responses — in formats compatible with high-throughput data acquisition Rigor & Reproducibility: Drive documentation, SOPs, and data standards that ensure reproducible, publication-quality results across the cardiac biology platform ML & Cross-functional Partnership Experiment Design for ML: Partner with ML and computational biology teams to design experiments that generate high-quality training data and to interpret model outputs in biological context Target Identification: Contribute to target identification and validation efforts by connecting cellular phenotypes to human genetic evidence Scientific Leadership Mentorship: Mentor junior scientists and technicians, and contribute to a collaborative, scientifically rigorous team culture About You Experience & Qualifications Advanced Degree: Ph.D. in cell biology, biomedical engineering, cardiac physiology, or a related field, with at least 3 years of industry experience iPSC-CM Expertise: Deep hands-on experience in iPSC culture, cardiac directed differentiation, and iPSC-CM characterization across both 2D and 3D/EHT platforms Genetic Disease Modeling: Track record building and applying genetic iPSC-CM disease models — patient-derived lines, CRISPR-edited isogenic pairs — to study cardiovascular mechanisms Cardiovascular Biology: Strong foundational knowledge of cardiomyocyte biology and cardiovascular disease High-Content Imaging: Experience with high-content imaging and/or automated microscopy platforms, including image analysis pipelines Human Genetics: Familiarity with GWAS and human genetic evidence, and experience using these data to prioritize disease mechanisms or therapeutic targets Scientific Communication: Track record of executing rigorous experiments and communicating findings clearly in publications, presentations, or internal reports Core Competencies ML Curiosity: You're enthusiastic about working alongside ML scientists and understand how experimental design shapes what a model can learn Builder Mentality: You thrive building systems from the ground up and bring the same rigor to a new workflow as to a published experiment Cross-functional Collaborator: You work fluidly across biology, computation, and chemistry, and communicate clearly across disciplines Independent & Adaptive: You drive projects forward independently in a fast-paced environment while staying aligned with team priorities Compensation & Benefits at insitro Our target starting salary for successful US-based applicants for this role is $156,000 - $166,000. To determine starting pay, we consider multiple job-related factors including a candidate's skills, education and experience, market demand, business needs, and internal parity. We may also adjust this range in the future based on market data. This role is eligible for participation in our Annual Performance Bonus Plan (based on company targets by role level and annual company performance) and our Equity Incentive Plan, subject to the terms of those plans and associated policies. In addition, insitro also provides our employees: 401(k) plan with employer matching for contributions Excellent medical, dental, and vision coverage as well as mental health and well-being support Open, flexible vacation policy Paid parental leave of at least 16 weeks to support parents who give birth, and 10 weeks for a new parent (inclusive of birth, adoption, fostering, etc) Quarterly budget for books and online courses for self-development New hire stipend for home office setup Monthly cell phone & internet stipend Access to free onsite baristas and daily lunch for employees who are either onsite or hybrid Access to a free commuter bus network that provides transport to and from our South San Francisco HQ from locations all around the Bay Area insitro is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status. We believe diversity, equity, and inclusion need to be at the foundation of our culture. We work hard to bring together diverse teams–grounded in a wide range of expertise and life experiences–and work even harder to ensure those teams thrive in inclusive, growth-oriented environments supported by equitable company and team practices. All candidates can expect equitable treatment, respect, and fairness throughout the interview process. Please be aware of recruitment scams: we never request payments, all recruitment communications are from @ insitro.com , and if in doubt, contact us at [email protected] . #LI-Onsite About insitro insitro is a drug discovery and development company using machine learning (ML) and data at scale to decode biology for transformative medicines. At the core of insitro’s approach is the convergence of in-house generated multi-modal cellular data and high-content phenotypic human cohort data. We rely on these data to develop ML-driven, predictive disease models that uncover underlying biologic state and elucidate critical drivers of disease. These powerful models rely on extensive biological and computational infrastructure and allow insitro to advance novel targets and patient biomarkers, design therapeutics and inform clinical strategy. insitro is advancing a wholly owned and partnered pipeline of insights and therapeutics in neuroscience and metabolism. Since launching in 2018, insitro has raised over $700 million from top tech, biotech and crossover investors, and from collaborations with pharmaceutical partners. For more information on insitro, please visit www.insitro.com .

Full job record

Job ID873a72faf0d6146e19728da3656cbd5a57179819
Org ID80106de1-ef22-4b6f-83b9-9f5555c24a57
Source ID917579bf-4831-4f84-894f-f8f55008e633
Board ID917579bf-4831-4f84-894f-f8f55008e633
Providerashby
Provider Job Key0aea232d-aaac-4a2f-b26e-6b1cf23f8466
TitleSenior Scientist, Cardiac Modeling
Normalized Title
Statusactive
Activeyes
Location TextSouth San Francisco, CA
DepartmentTherapeutic Areas
TeamTherapeutic Areas, Metabolic Diseases
Employment Typefull_time
Workplace Typehybrid
Remote Policyhybrid
CountryUnited States
RegionCA
CitySouth San Francisco
Salary RawCompensation & Benefits at insitro Our target starting salary for successful US-based applicants for this role is $156,000 - $166,000. To determine starting pay, we consider multiple job-related factors including a
Salary Min156,000
Salary Max166,000
Salary CurrencyUSD
Salary Periodyear
Source URLhttps://jobs.ashbyhq.com/insitro/0aea232d-aaac-4a2f-b26e-6b1cf23f8466
Apply URLhttps://jobs.ashbyhq.com/insitro/0aea232d-aaac-4a2f-b26e-6b1cf23f8466/application
First Seen At2026-06-17 10:09:40Z
Last Seen At2026-06-19 09:26:12Z
Last Checked At2026-06-19 09:26:12Z
Last Changed At2026-06-17 10:09:40Z
Inactive At
Source Posted At
Source Updated At
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Extensions
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Native Structured
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