SandboxAQ
AI Solutions
StaffResearchScientist,CatalystSimulation
Neural analysis suggests this role is
optimal for Senior candidates.
“Staff Research Scientist, Catalyst Simulation at SandboxAQ. Skills: Catalyst Simulation, Microkinetic Modeling, Reactor Modeling, Machine Learning. Design microkinetic and reactor-level modeling workflows. Translate energetics into process-scale observables”
What You'll Achieve.
Advance catalyst technologies; Accelerate catalyst concept movement; Deliver decision-ready results
Industry & Context.
Translate partner problems into modeling targets
What They're Looking For.
Must Have
PhD in Chemical Engineering, Chemistry, Materials Science, or related field, 6+ years post-PhD experience in microkinetic modeling, Coupling atomistic energetics to reactor-level predictions, Publication or patent record in DFT-derived energetics, Publication or patent record in microkinetic modeling, Publication or patent record in reactor-scale integration, Proficient in Python, Modern scientific software practices in HPC, Comfortable working with ML-trained force fields, Comfortable working with foundation models, Lead application-driven scientific engagements, Communicate results to non-specialist audiences, US Person (Permanent Resident or Citizen)
Nice to Have
Direct experience with semiconductor-relevant catalytic chemistries, Experience with operando or in-situ characterization data, Familiarity with Bayesian optimization, Familiarity with active learning, Familiarity with uncertainty quantification, Experience operating in CHIPS Act program, Experience operating in federally funded R&D program
What You'll Do.
Design microkinetic and reactor-level modeling workflows
Translate energetics into process-scale observables
Lead application engagements with industrial partners
Translate partner problems into modeling targets
decision-ready results
Partner with internal teams to specify energetics
Partner with internal teams to specify descriptors
Partner with internal teams to specify uncertainty estimates
Close loop between reaction-scale and process-scale modeling
Validate models against experimental data
Drive iterative model refinement
Drive uncertainty quantification
Mentor junior research scientists
Contribute to publications
Contribute to partner deliverables
Shape technical roadmap for microkinetic modeling
How You'll Work.
Team & Collaboration
Cross-functional collaboration; Partner with industrial validation partners; Partner closely with internal teams
Communication Scope
Communicate results; Technical roadmap
Full Job Description
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 Introduction to the team: The Catalysis team develops and validates new catalyst technologies for complex industrial applications, with a focus on high-purity chemical production, emissions treatment, and advanced sensing. The team brings together computational modeling, machine learning, experimental validation, and cross-functional collaboration to accelerate how promising catalyst concepts move from discovery to real-world use. Introduction to the role: The Catalysis team is looking for a Staff Research Scientist, Catalyst Simulation to lead the translation of reaction energetics derived from atomistic simulations and machine learning potentials into process-scale predictions that advanced manufacturing facilities, OEMs, and chemical manufacturers can act on. This person will: (1) own the design and execution of microkinetic and reactor-level modeling workflows for industrially relevant catalytic chemistries, (2) connect atomistic simulation outputs to a
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