
Job 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.
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Job Details
- Category
- Research
- Employment Type
- Full Time
- Location
- South San Francisco, CA
- Posted
- Compensation
- $156,000 - $166,000 per year
About Insitro
insitro is the AI therapeutics company built on causal biology. By generating an integrated, multimodal corpus of human and cellular data and analyzing it with machine learning, insitro's platform aims to reveal how disease begins, progresses, and can be resolved. The company applies this approach to identify genetic drivers, prioritize targets, and design medicines intended to treat disease at its root, with programs focused in metabolic disease and neuroscience. insitro was founded by Daphne Koller and operates through a bilingual culture – cross-functional collaboration where machine learning scientists, discovery biologists, and drug hunters work as a single integrated unit. The company established partnerships with Bristol Myers Squibb, Eli Lilly, and Gilead, and is backed by world-class investors. insitro brings together expertise across computational biology, human genetics, bioengineering, automation, and drug discovery to help bring effective medicines to patients faster. Join us in transforming drug discovery and development!
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