Research Scientist, Catalyst Simulation

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Salary

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401(k) match

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Market context

Median wage (BLS OEWS)

$111,944 national median

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

Shift type

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Weekend work

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Application

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Assessment

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Deadline

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Where they hire

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About this role

Research Scientist, Catalyst Simulation United States 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 As a Research Scientist on our Computational Catalysis team, you will join a dedicated team of subject matter experts, computational scientists, software developers, and machine learning experts, leveraging an ensemble of state-of-the-art proprietary computational tools to solve real-world challenges. In this flexible role, you will be responsible for supporting one or more of the following core focus areas: - Developing large-scale DFT datasets and machine learning potentials for heterogeneous catalysis. - Supporting the design and implementation of computational workflows simulating the reactivity and dynamics of catalytic materials at atomic, mesoscale, and continuum scales. - Supporting heterogeneous catalyst discovery and optimization projects with

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