About SandboxAQ
SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors.
We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders.
At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact.
The Opportunity
You will join a multidisciplinary team of computational biologists, AI experts, and physicists dedicated to building next-generation computational biology models. Our team focuses on translating complex biological reality into transparent, causal frameworks to reshape the drug discovery and development pipeline.
The BioSim Team is looking for a Research Scientist, Quantitative Systems Biology to join our team. This role is central to our efforts to: anchor our computational models in deep Systems and Cellular Biology expertise, translating experimental data into predictive world models.
This person will achieve the following goals:
Formalize biological knowledge by translating literature and multi-omics datasets into cell-type-aware causal and reaction-level frameworks.
Drive experimental validation by selecting precise assays and readouts that close the loop between model predictions and biological reality.
Apply model outputs to drug discovery, specifically for target identification, mechanism of action (MoA) inference, and cell-type-specific toxicity.
This is an opportunity to lead the creation of a novel benchmark suite for causal biological world models, moving beyond "black box" AI to build reproducible, regulatory-grade mechanistic frameworks that impact global health.
Key Responsibilities
Formalize Causal Frameworks: Translate complex literature and datasets into structured, reaction-level frameworks for modeling, ensuring all mechanisms capture molecular context and regulation.
Design & Validate Models: Collaborate with AI teams to design perturbation-response models that enforce biological plausibility, uncertainty reporting, and traceability.
Guide Data Interpretation: Lead the interpretation of multi-omics data (single-cell, spatial, proteomic), accounting for experimental biases and limitations to ground models in real biology.
Bridge Theory and Experiment: Turn model outputs into precise hypotheses to drive experimental priorities; feed results back into models to refine mechanism curation.
Maintain Knowledge Systems: Build a living knowledge base of biological mechanisms and assumptions to support reproducibility and regulatory-grade audits.
Essential Skills & Experience
PhD and 1–3 years of experience (postdoc or industry) in molecular, cellular, quantitative, or systems biology applying mechanistic biology to computational research.
Python Proficiency: Demonstrated ability to write Python code for exploratory data analysis and visualization.
Causal Graph Construction: Proven ability to formalize biological mechanisms into structured causal representations for computational modeling.
Multi-Omics Expertise: Strong conceptual understanding of transcriptomic, single-cell, spatial, and proteomic data, including awareness of experimental biases (batch effects, noise).
Collaborative Modeling: Experience partnering with data scientists to refine predictive models for therapeutic discovery or target identification.
Highly Desired Skills & Experience
Mechanistic Modeling for Therapeutics: Expertise in applying GRNs, ODEs, or Systems Pharmacology to predict perturbation outcomes and test model validity.
Virtual Cell Engineering: Experience developing or rigorously evaluating virtual cell models to uncover mechanistic explanations for simulated drug responses.
Translational Context: Familiarity with modeling challenges in drug toxicity (ADME/Tox) and late-stage clinical data.
Cross-Functional Strategy: Experience aligning modeling strategies and experimental design across scientific, engineering, and business teams.
Integrative Synthesis: Hands-on experience integrating diverse multi-modal data to generate unified biological insights.
Why Join Us?
We offer a comprehensive and competitive benefits package designed to support your health, financial well-being, and life outside of work.
Compensation: Competitive base salary, performance-based incentives or bonuses (where applicable), and equity participation.
Benefits: Comprehensive medical, dental, and vision coverage for employees and dependents with generous employer premium contributions, retirement savings with company matching, paid parental leave, and inclusive family-building benefits.
Work-Life Balance: Flexible paid time off, company-wide seasonal breaks, and support for flexible work arrangements that enable sustainable performance.
Career Development: Opportunities for continuous learning and growth through on-the-job development, cross-functional collaboration, and access to internal learning and development programs.
SandboxAQ Welcomes All
We are committed to fostering a culture of belonging and respect, where diverse perspectives are actively sought and valued. Our multidisciplinary environment provides ample opportunity for continuous growth - working alongside humble, empowered, and ambitious colleagues ready to tackle epic challenges.
Equal Employment Opportunity: All qualified applicants will receive consideration regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status.
Accommodations: We provide reasonable accommodations for individuals with disabilities in job application procedures for open roles. If you need such an accommodation, please let a member of our Recruiting team know.
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