Battery Machine Learning Force Fields Scientist

Schrödinger seeks a Battery Machine Learning Force Fields Scientist to aid us in our mission to improve human health and quality of life through the development, distribution, and application of advanced computational methods.

As a member of our Machine Learning team, you’ll play a key role in developing a next generation simulation platform for battery materials and testing the limits of classical approximations to quantum mechanics. You’ll also have the opportunity to communicate and collaborate with team members across many different departments and disciplines.

Who will love this job:

• An innovator who wants to contribute to leading battery chemistry simulation models
• An independent researcher who enjoys collaborating with an interdisciplinary team in a fast-paced environment
• A computational scientist who wants to push the limits of what can be simulated at the atomic level
• An excellent communicator and documenter who has experience collaborating teams of diverse scientists

What you’ll do:

• Develop new atomistic machine learning force fields with improved accuracy and generalization
• Contribute to a platform to simulate chemical processes at the electrode/electrolyte interface and discover new battery materials
• Generate and train on sets of millions of quantum chemistry simulations
• Apply best practices from the world of software engineering
• Build scientific validation tests to ensure models continue to perform well

What you’ll need:

• PhD in Chemistry, Materials Science, Chemical Engineering, Physics, or a related field or a scientific degree plus two to three years' relevant industry experience
• Background in applying molecular simulation and quantum chemistry methods

We’d prefer to hire someone with:

• Experience developing interatomic potentials based on machine learning or classical force fields
• Expertise in the simulation of electrode and electrolyte materials, interfaces, and ion transport
• Familiarity with enhanced sampling, rare-event sampling, or transition state search methods
• Proficiency with Python libraries such as NumPy, SciPy, and PyTorch

Pay and perks:

Schrödinger understands it’s people that make a company great. Because of this, we’re prepared to offer a competitive salary, stock options, 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. 

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.