We’re seeking a Computational Materials Scientist in 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 growing Materials Science Discovery team, you’ll focus on developing data-driven models using physics and machine learning to provide predictive solutions for optimizing 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 chemist with a solid understanding of electronic structure methods, surface reactivity calculations, and chemical kinetics, as well as a proven track record in electronic structure simulations for heterogeneous catalysis
- A proven 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
- Establish best practices for reactivity simulations to advise internal and external collaborators
What you’ll need:
- PhD in Physical Chemistry, Computational Chemistry, Quantum Chemistry, Materials Science, Engineering, Physics, or a related scientific discipline
- Microkinetic modeling and kinetic Monte Carlo background
- Familiarity with ab initio molecular dynamics
- Experience using periodic DFT codes to study the electronic structure of solids, surface properties, and heterogeneous catalytic reactions and kinetics
- Python programming proficiency is a plus
- Experience with machine learning potentials and periodic xTB is a plus
Pay and perks:
Schrödinger understands it’s people that make a company great. Because of this, we’re prepared to offer a competitive salary, equity-based compensation, and a wide range of benefits that include healthcare (with dental and vision), a 401k, pre-tax commuter benefits, a flexible work schedule, and a parental leave program. We have regular catered meals in the office, a company culture that is relaxed but engaged, and over a month of paid vacation time. Our Office Management team also plans a myriad of fun company-wide events. New York is home to our largest office, but we have teams all over the world. Schrödinger is honored to have been included in Crain's New York Best Places to Work, BuiltIn's NYC Best Place to Work, and Newsweek's list of America's 100 Most Loved Workplaces.
Estimated base salary range: $120,000 - $170,000. Actual compensation package is dependent on a number of factors, including, for example, experience, education, degrees held, market data, and business needs. If you have any questions regarding the compensation for this role, do not hesitate to reach out to a member of our Strategic Growth team.
Sound exciting? Apply today and join us!
As an equal opportunity employer, Schrödinger hires outstanding individuals into every position in the company. People who work with us have a high degree of engagement, a commitment to working effectively in teams, and a passion for the company's mission. We place the highest value on creating a safe environment where our employees can grow and contribute, and refuse to discriminate on the basis of race, color, religious belief, sex, age, disability, national origin, alienage or citizenship status, marital status, partnership status, caregiver status, sexual and reproductive health decisions, gender identity or expression, sexual orientation, or any other protected characteristic. To us, "diversity" isn't just a buzzword, but an important element of our core principles and key business practices. We believe that diverse companies innovate better and think more creatively than homogenous ones because they take into account a wide range of viewpoints. For us, greater diversity doesn't mean better headlines or public images - it means increased adaptability and profitability.
