Research Scientist, Homogeneous Catalyst Simulation

SandboxAQ

United States

On-site

USD 150,000 - 190,000

Full time

14 days+

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Benefits offered by this job

Remote work

Job summary

SandboxAQ in the United States is seeking a Research Scientist for the Computational Catalysis team to apply state-of-the-art atomistic methods and ML to homogeneous catalysis challenges. You will design workflows, develop large datasets and ML models, and collaborate with software and ML teams to advance discovery and optimization for industrial partners.

Strong publication record and ability to mentor junior scientists are valued, with remote-friendly work and opportunities for

Qualifications

  • PhD in chemistry, chemical engineering, materials science, or related field.
  • Experience with modern atomistic simulation methods for homogeneous catalysis.
  • Experience in silico catalyst discovery/optimization and mechanism elucidation.
  • Strong Python skills for computational chemistry and reaction analysis in HPC.
  • Record of interdisciplinary collaboration and publications.

Responsibilities

  • Design and implement computational workflows for catalytic cycles and selectivity.
  • Collaborate with platform, ML, and software teams to improve workflows.
  • Develop datasets and ML models for catalysis discovery and reaction optimization.
  • Mentor junior scientists and present findings to internal and external partners.

Skills

Atomistic simulations
In silico catalyst design
Python for computational chemistry
Interdisciplinary collaboration
Publications record

Education

PhD in Chemistry, Chemical Engineering, or Materials Science

Tools

Python
Open-source software
HPC

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

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 role, you will be responsible for supporting one or more of the following core focus areas:

  • 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 our industrial partners in the chemical, pharmaceutical, and energy sectors.

  • Developing large-scale quantum chemistry datasets and machine learning models for homogeneous catalysis.

Key Responsibilities
  • Project & Client Leadership

    • Support client engagements focused on the research, development, discovery, and optimization of novel homogeneous catalysts, ligands, and reaction conditions.

    • Support business functions with technical diligence and proposal development for pre-sales customer engagements.

  • Technical Execution & Innovation

    • Deploy and support the design and implementation of computational workflows to investigate catalytic cycles, elementary reaction steps, transition states, catalyst speciation, and structure-selectivity relationships in homogeneous catalysis.

    • Collaborate with platform, machine learning, and software engineering teams to continuously improve the efficiency and performance of discovery workflows.

    • Develop large-scale datasets and machine-learned models for molecular catalyst and reaction discovery.

  • Communication & Mentorship

    • Prepare and deliver high-impact reports, presentations, and publications to communicate research findings to internal, academic, and industry partners.

    • Mentor junior scientists and interns in catalysis, reaction engineering, and computational methods, championing best research and software practices.

Essential Skills & Experience
  • PhD in Chemistry, Chemical Engineering, Materials Science, or an equivalent/related discipline, or equivalent 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 software development with Python, particularly for computational chemistry and reaction analysis, and experience implementing open-source packages in an HPC environment.

  • Ability to collaborate effectively within diverse, interdisciplinary teams.

  • A strong publication record demonstrating interdisciplinary collaboration and the ability to adapt to new technologies and methodologies in catalysis research.

Highly Desired Skills & Experience
  • 3+ years of proven industrial R&D experience supporting experimental groups with computational studies for homogeneous catalyst discovery, mechanism elucidation, or selectivity optimization.

  • Hands-on experience or familiarity with experimental methods for homogeneous catalysis research (e.g., organometallic synthesis, reaction screening, spectroscopy, and mechanistic studies).

  • Experience developing software in an industrial setting as part of a software engineering team, with familiarity with software development best practices like Agile.

  • Willingness to travel occasionally for in-person meetings with industrial partners.

Why Join Us?

We offer competitive compensation, a comprehensive benefits package, and opportunities for professional growth.

  • Compensation: Competitive base salary, performance-based incentives or bonuses (where applicable), and equity participation.

  • Benefits: Comprehensive medical, dental, and vision coverage for employees and dependents with generous employer premium contributions, retirement savings with company matching, paid parental leave, and inclusive family-building benefits.

  • Work-Life Balance: Fully remote, Flexible paid time off, company-wide seasonal breaks, and support for flexible work arrangements that enable sustainable performance.

  • Career Development: Opportunities for continuous learning and growth through on-the-job development, cross-functional collaboration, and access to internal learning and development programs.

SandboxAQ Welcomes All

We are committed to fostering a culture of belonging and respect, where diverse perspectives are actively sought and valued. Our multidisciplinary environment provides ample opportunity for continuous growth - working alongside humble, empowered, and ambitious colleagues ready to tackle epic challenges.

Equal Employment Opportunity: All qualified applicants will receive consideration regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status.

Accommodations: We provide reasonable accommodations for individuals with disabilities in job application procedures for open roles. If you need such an accommodation, please let a member of our Recruiting team know.

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