SandboxAQ · 2 months ago
Staff Research Scientist, Quantitative Systems Biology
United States
Full-time
Remote
Senior Level, Lead/Staff
$179K/yr - $251K/yr
1+ years expSandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. We are seeking a highly skilled Research Scientist to anchor our next-generation computational biology models in deep Systems and Cellular Biology expertise, leveraging experimental data to enable cutting-edge computational modeling.
Artificial Intelligence (AI)Cyber SecurityInformation TechnologyQuantum ComputingSaaS
Responsibilities
Formalize biological knowledge by translating literature and datasets into cell-type-aware causal and reaction-level frameworks for modeling
Turn observations and model outputs into precise hypotheses and acceptance criteria that drive assay selection and experimental priorities
Collaborate with modeling teams to design and validate perturbation-response models enforcing biological plausibility, uncertainty reporting, and traceability
Guide interpretation of multi-omics data, accounting for experimental limitations and biases to ground models in real biology
Drive experimental validation with partners by selecting assays and readouts, then close the loop by feeding results back into models and mechanism curation
Apply model outputs to drug discovery problems, including target identification, mechanism of action inference, and prediction of cell-type-specific toxicity
Build and maintain a living knowledge base of mechanisms, provenance, and assumptions to support reproducibility and regulatory-grade audits
Work closely with the team to establish a novel benchmark suite for causal biological world models
Qualification
Required
PhD and Applied Work Experience in Quantitative Biology. PhD in molecular, cellular, quantitative, or systems biology with 1–3 years of postdoctoral or industry experience (biotech, pharma, or techbio) applying mechanistic biology to data-driven or computational research
Proficiency in Python for Data Analysis. Demonstrated ability to write Python code for exploratory data analysis, and visualization
Collaboration with Computational Biologists on Therapeutic Discovery Models. Experience partnering with data scientists and modelers to interpret, validate, and refine causal or predictive models for therapeutic discovery, target identification, or off-target assessment
Construction and Curation of Causal or Reaction-Level Graphs for Modeling. Proven ability to extract, reconcile, and formalize biological mechanisms into structured causal or reaction-level representations that accurately capture regulation, modification, and molecular context for computational modeling
Multi-Omics Data Integration and Understanding of Experimental Bias. Strong conceptual understanding of transcriptomic, single-cell, spatial, and proteomic data, including awareness of experimental limitations, data biases (batch effects, noise), and how these affect mechanistic inference and biological model accuracy
Preferred
Mechanistic Modeling for Therapeutics: Expertise in conceptualizing or applying quantitative models (e.g., GRNs, ODEs, Systems Pharmacology) to predict perturbation outcomes. Proven experience with causal inference/graph-based reasoning and applying structured benchmarks to test model validity and interpretability
Integrative Multi-Omics and Data Synthesis: Hands-on experience integrating diverse multi-modal data (e.g., transcriptomic, proteomic, spatial, single-cell) to generate unified insights and contextualize model predictions
Virtual Cell Model Engineering: Experience developing, interpreting, or rigorously evaluating virtual cell models to uncover mechanistic explanations and improve the fidelity of simulated drug response predictions
Translational/Clinical Context: Familiarity with the data and modeling challenges specific to drug toxicity (ADME/Tox) and late-stage clinical data, addressing the high-cost-of-guesswork failure mode
Cross-Functional Strategy and Alignment: Experience collaborating across scientific, engineering, and business teams to align modeling strategies, experimental design, and translational objectives
Benefits
Annual discretionary bonuses
Equity
Competitive salaries
Stock options depending on employment type
Generous learning opportunities
Medical/dental/vision
Family planning/fertility
PTO (summer and winter breaks)
Financial wellness resources
401(k) plans
More
Company
SandboxAQ
SandboxAQ develops AI and quantum technology solutions that enhance biopharma, cybersecurity, and materials science.
51-200 employees
H1B Sponsorship
SandboxAQ has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (7)
2024 (6)
2023 (3)
2022 (5)
2021 (1)
2020 (5)
Funding
Current Stage
Late StageTotal Funding
$975MKey Investors
Eric Schmidt Angel InvestmentsMichael J. Fox Foundation
2025-04-04Series E· $150M
2024-12-18Series E· $300M
2024-10-29Grant· $25M
Leadership Team
Jack Hidary
Chief Executive Officer
Joerg Rathenberg
Head Of Marketing
Recent News
2025-12-30
Fast Company Middle East | The future of tech, business and innovation.
2025-12-24
Company data provided by crunchbase