Computational Scientist (Catalysis)
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.
About the Role
In this role, you will be responsible for developing and deploying computational methods for the design and optimization of catalytic materials. You will work closely with a team of subject matter experts, computational scientists, software developers, and machine learning experts using an ensemble of state of art proprietary tools. Material domains include and are not limited to chemical manufacturing processes, energy solutions, and other industrial applications.
Core Responsibilities
- Lead design and implementation of computational workflows simulating reactivity and dynamics of catalytic materials at atomic, mesoscale, and continuum scales.
- Prepare reports, presentations, and publications to communicate research findings to internal, academic, and industry partners.
- Support business functions in materials science pre-sales customer technical diligence and proposals.
- Support client engagements on the research and development of novel materials.
- Collaborate with software engineering to improve efficiency and performance of discovery workflows.
- Mentor junior scientists and interns in computational methods, ensuring best research and software practices.
About You
- PhD in Chemical Engineering, Materials Science, Chemistry or a related discipline
- Extensive experience concerning in silico catalyst discovery (heterogeneous or homogeneous) and optimization with 1-4 years of post-PhD experience, including at least 1 year in an industry environment.
- Proven experience providing in silico support to experimental groups working on catalyst design and/or optimization, including microkinetic modeling.
- Hands-on experience in developing machine-learned force fields for materials discovery.
- Strong background in software development with Python, particularly for computational materials analysis, and experience implementing open-source packages in an HPC environment.
- Ability to collaborate effectively within interdisciplinary teams.
Nice-to-Haves
- Experience or coursework in AI/ML.
- Experience developing software in an industrial setting as part of a software engineering team.
- Familiarity with software development best practices (e.g., Agile).
- Quick learner with the ability to adapt to emerging technologies, methodologies, and advancements in catalysis research.
The US base salary range for this full-time position is expected to be $150k-$245k per year. Our salary ranges are determined by role and level. Within the range, individual pay is determined by factors including job-related skills, experience, and relevant education or training. This role may be eligible for annual discretionary bonuses and equity.