Computational Materials Scientist in Catalysis and Reactivity bei Schrödinger

We’re seeking a Computational Materials Scientist in Heterogeneous Catalysis and Reactivity to join us in our mission to improve human health and quality of life through developing, distributing, and applying advanced computational methods.

As a member of our Materials Science team, you’ll focus on developing data-driven models using physics and machine learning to provide predictive solutions for optimizing heterogeneous catalyst materials and associated processes, with a strong commercialization focus. Using your passion for analysis, optimization, and discovery of tailored reactive systems using quantum mechanical simulations, you’ll play a key role in advancing groundbreaking research.

Who will love this job:

• An experienced computational scientist with a proven track record in computational heterogeneous catalysis, including electronic structure methods, surface reactivity calculations, and chemical kinetics 
• An established researcher who enjoys working independently and as part of a team
• An excellent communicator with outstanding interpersonal and organizational skills

What you’ll do:

• Collaborate with internal and external stakeholders on computationally-driven catalysis materials discovery, analysis, and optimization using a combination of atomic-scale simulations and machine learning to analyze and model catalyst materials and processes
• Build predictive catalyst performance models based on physics-based simulation and experimental data

What you’ll need:

• PhD in Physical Chemistry, Computational Chemistry, Quantum Chemistry, Materials Science, Engineering, Physics, or a related scientific discipline
• Experience in heterogeneous catalysis and using periodic DFT codes to study the electronic structure of solids, surface properties, and heterogeneous catalytic reactions and kinetics
• Experience with microkinetic modeling and machine learning in surface chemistry is a plus
• Python programming proficiency is a plus