Sr Research Scientist, Materials Simulation

Ready to join the AQ era?

SandboxAQ is solving challenging problems with AI + Quantum for positive impact. We partner with global leaders in government, academia, and the private sector to identify applications that would benefit from quantum-based applications to current and future commercial challenges. We engage with customers early and throughout the development process to improve market fit.

Our team’s unique approach enables cross-pollination across a diverse range of fields, from physics, computer science, neuroscience, mathematics, cryptography, natural sciences and more! Our success comes from coalescing diverse talent to create an environment where experimental thinking and collaboration yield breakthrough AI + Quantum solutions. Join a culture where thought leadership, diverse talent, employee engagement, and technological impact will create the next tech uproar.

We are deeply committed to education as a means to advance quantum solutions and computing initiatives. We invest in future talent through internship programs, research papers, developer tools, textbooks, educational talks/events and partnerships with universities/talent hubs to attract multi-disciplinary talent. Our hope is to inspire people from all walks of life to be prepared for the quantum era and encourage a path in STEM.

About the Team

The Simulation and Optimization (S&O) team develops AI and quantum solutions for computational science, with a near-term focus on materials design, discovery, and development. We seek revolutionary impact on human health, the environment, and the economy. S&O researchers will develop and implement novel physics-based, AI, quantum, and quantum-inspired algorithms for materials design and beyond. Working closely with a focused team of PhDs, MBAs, engineers, and product experts, you will confront hard social problems, make business impact, and improve lives.

About the Role

We are seeking a highly skilled and experienced Sr. Research Scientist in Materials Simulation to join our dynamic team. The ideal candidate will have a strong background in applying advanced simulation techniques, particularly Density Functional Theory (DFT) and Molecular Dynamics (MD), to solid-state materials, with a focus on metal alloys and catalyst materials. Additionally, expertise in machine learning and coding is essential, particularly in the development of machine learning force fields for solid-state materials.

Key Responsibilities

• Conduct advanced simulations using DFT and MD for solid-state materials, with a focus on metal alloys and catalysts.
• Develop and implement machine learning algorithms, specifically in the area of solid-state materials.
• Work on the development and refinement of machine learning force fields for solid-state materials.
• Employ data-driven approaches to analyze large datasets derived from computational simulations and experiments to uncover new insights into materials behavior.
• Guide and scope projects with clear deliverables alongside agile teams.
• Collaborate closely with multi-disciplinary teams to independently prototype and scale cutting-edge, impactful materials design solutions.

• Generate and evaluate hypotheses to assist design decisions and influence project direction by developing and deploying computational methods and workflows. 
• Effectively present and communicate research findings through talks, blog posts, clients and scientific publications.

Basic Qualifications

• M.S. with 2-3 years of work experience or Ph.D. in Materials Science, Physics, Chemistry, Computer Science, or a related field is preferred.
• Strong theoretical foundation in thermodynamics, particularly in understanding and analyzing phase diagrams of complex materials.
• Proficiency in common DFT and MD simulation software (e.g., VASP, Quantum ESPRESSO, LAMMPS)
• Experience in developing and validating machine learning models for material property predictions.
• Proficiency in programming languages (e.g., Python) and tools relevant to AI and data analysis (e.g., scikit-learn, TensorFlow, PyTorch).
• Experience with deploying ML models on public cloud computing infrastructure (e.g. GCP, AWS, Azure).
• Experience in one or more of the following ML applications to materials discovery or materials science: chemical space exploration, reinforcement learning, active learning, generative methods for chemistry, ML force fields, crystal structure prediction, reaction pathway prediction, QSAR, similarity search, chemical space visualization, ADME ML predictions, chemical clustering, knowledge graphs, and/or foundation models.
• Demonstrated ability in project leadership within an industrial setting, including managing teams, timelines, and deliverables.
• Excellent problem-solving skills and the ability to work independently and collaboratively.
• Excellent communication and collaboration skills with people of diverse backgrounds and job functions. 

Preferred Qualifications

• At least 3-5 years of industry and hands-on experience in modeling complex solid-state material systems, such as high entropy alloys or multi-component composites, at high temperatures is highly desirable
• Experience developing machine learning force fields for solid-state systems is a plus.
• Authorship of publications in high impact peer-reviewed journals or conferences.
• Experience creating and improving novel machine learning methods applied to materials discovery problems with a track record of success.

SandboxAQ welcomes all.

We are committed to creating an inclusive culture where we have zero tolerance for discrimination. We invest in our employees' personal and professional growth. Once you work with us, you can’t go back to normalcy because great breakthroughs come from great teams and we are the best in quantum technology.   We offer competitive salaries, stock options depending on employment type, generous learning opportunities, medical/dental/vision, family planning/fertility, PTO (summer and winter breaks), financial wellness resources, 401(k) plans, and more.    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.