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SandboxAQ is a high-growth AI company delivering Large Quantitative Models (LQMs) that address challenges in life sciences, financial services, navigation, cybersecurity, and other sectors. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022.
As a Research Scientist on the Computational Catalysis team, you will work with subject matter experts, computational scientists, software developers, and machine learning engineers to solve real-world challenges in homogeneous catalyst discovery and optimization.
Key responsibilities include:
- Supporting the design and implementation of computational workflows to study reaction mechanisms, catalyst speciation, selectivity, and reactivity in molecular catalytic systems.
- Supporting homogeneous catalyst discovery and optimization projects with industrial partners in chemical, pharmaceutical, and energy sectors.
- Developing large-scale quantum chemistry datasets and machine learning models for homogeneous catalysis.
- Supporting client engagements focused on research, development, discovery, and optimization of novel homogeneous catalysts, ligands, and reaction conditions.
- Deploying computational workflows to investigate catalytic cycles, elementary reaction steps, transition states, and structure-selectivity relationships.
- Collaborating with platform, machine learning, and software engineering teams to improve discovery workflow efficiency and performance.
- Preparing and delivering reports, presentations, and publications to communicate research findings to internal, academic, and industry partners.
- Mentoring junior scientists and interns in catalysis, reaction engineering, and computational methods.
Required qualifications:
- PhD in Chemistry, Chemical Engineering, Materials Science, or equivalent discipline/practical experience.
- Experience developing and utilizing modern atomistic simulation methods for homogeneous catalysis, including quantum chemistry, machine learning potentials, reaction-path analysis, kinetics, and data-driven models.
- Experience performing in silico catalyst discovery and/or optimization projects with emphasis on molecular catalyst design, mechanism elucidation, and selectivity control.
- Strong background in Python software development for computational chemistry and reaction analysis, with experience implementing open-source packages in HPC environments.
- Ability to collaborate effectively within diverse, interdisciplinary teams.
- Strong publication record demonstrating interdisciplinary collaboration and adaptability to new technologies and methodologies in catalysis research.
Highly desired:
- 3+ years of industrial R&D experience supporting experimental groups with computational studies for homogeneous catalyst discovery.
- Hands-on experience or familiarity with experimental methods for homogeneous catalysis research (organometallic synthesis, reaction screening, spectroscopy, mechanistic studies).
- Experience developing software in an industrial setting as part of a software engineering team, with familiarity with Agile practices.
- Willingness to travel occasionally for in-person meetings with industrial partners.
The company offers competitive base salary, performance-based incentives, equity participation, comprehensive medical/dental/vision coverage, retirement savings with company matching, paid parental leave, fully remote work, flexible PTO, and professional development opportunities.
