Senior Research Scientist, Catalyst Discovery

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Sandbox

AQ 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.

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AQ, 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.

You will join a dedicated group of subject matter experts, computational scientists, and ML experts focused on solving real-world challenges in the chemical and energy sectors. Our team leverages an ensemble of proprietary computational tools to revolutionize heterogeneous catalyst discovery and optimization for our industrial partners.

The AI Simulation Team is looking for a Senior Research Scientist, Catalyst Discovery to join our team. This role is central to our efforts to:
lead client engagements and deploy state-of-the-art computational workflows to discover and optimize novel heterogeneous catalyst materials.

This person will achieve the following goals:

• Lead high-impact client engagements focused on the discovery of novel catalyst materials, bridging the gap between proprietary simulations and industrial needs.

• Deploy multiscale computational workflows to simulate reactivity and dynamics across atomic, mesoscale, and continuum scales.

• Support commercial growth by providing technical diligence and proposal development for pre-sales customer engagements.

Why Join Us? You will be at the forefront of the chemical and energy transition, working in a multidisciplinary environment where your research practices and mentorship will shape the next generation of catalysis discovery.

• Lead Project & Client Engagements: Direct technical collaborations with industrial partners to optimize heterogeneous catalysts, serving as the primary lead for project delivery and research findings.

• Execute Technical Innovation: Deploy proprietary workflows to simulate catalytic materials and collaborate with engineering teams to improve the efficiency of discovery platforms.

• Support Business Development: Assist business functions with technical diligence, feasibility assessments, and proposal development for high-value pre-sales engagements.

• Communicate & Publish: Prepare high-impact reports and presentations for internal and external stakeholders, maintaining a presence in the academic and industry community through publications.

• Mentor & Champion Best Practices: Provide guidance and mentorship to junior scientists and interns in catalysis and reaction engineering, ensuring the highest standards of research.

• PhD in Chemical Engineering, Chemistry, or an equivalent discipline (or equivalent practical experience).

• 3+ years of industrial R&D experience specifically in heterogeneous catalysis and/or reaction engineering.

• Microkinetic Modeling: Direct experience developing and utilizing microkinetic models in collaboration with lab experiments for catalyst design.

• Computational Familiarity: Familiarity with modern atomistic simulation methods for catalyst discovery (via direct use or close collaboration).

• Technical Communication: A strong publication record demonstrating interdisciplinary collaboration and the ability to adapt to new methodologies.

• Programming: Basic programming skills, including familiarity with Python
  .

• DFT Expertise: Proven experience supporting experimental groups with DFT-based atomistic simulations for catalyst discovery.

• Expe…