Role Overview
Schrödinger is hiring a Machine Learning Force Field Scientist. This is a full-time role in New York. Part of Schrödinger's Data Science hiring, posted 3 weeks ago. Full responsibilities, required qualifications, and the apply link are listed in the description below.
Salary Context
Salary is not disclosed in this posting. Market median for Data Science roles is $160k-$220k (based on 352 comparable listings). Many employers share specifics during the interview process or after an initial screen.
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Job description
We’re seeking a Machine Learning (ML) Scientist to join us in our mission to transform the discovery of therapeutics and materials.
Schrödinger has pioneered a physics-based software platform that enables discovery of high-quality, novel molecules for drug development and materials applications more rapidly and at lower cost compared to traditional methods. The software platform is used by biopharmaceutical and industrial companies, academic institutions, and government laboratories around the world. Our multidisciplinary drug discovery team also leverages the software platform to advance collaborative programs and its own pipeline of novel therapeutics to address unmet medical needs.
As a member of our Machine Learning team, you’ll develop state-of-the-art ML force fields targeting impactful applications in Life and Materials sciences.
Who will love this job:
- An ML force fields expert who has developed, validated, and applied ML force fields to simulate complex condensed-phase systems, such as solid-liquid interfaces, reactive events in the condensed phase, or solvated biomolecules
- An innovator who’s driven to leverage technical knowledge to make a tangible impact
- A scientist with deep knowledge of both finite system and periodic DFT, as well as other electronic structure methods, and who understands the limitations and appropriate applications of these methods
- A proficient Python programmer with prior knowledge of ML toolkits such as PyTorch, Scikit-Learn, NumPy, SciPy, and Pandas
- An independent researcher who enjoys collaborating with an interdisciplinary team in a fast-paced environment
What you’ll do:
- Build and manage large data sets generated using quantum chemical methods at scale to develop predictive ML force fields
- Develop software that trains and applies ML force fields to challenging problems in life and materials sciences
- Extend the accuracy, capability and generalization of current ML force fields
- Communicate results and present ideas to the team
What you should have:
- A PhD (or extensive experience) in Chemistry, Materials Science, Engineering, Computer Science, or Physics
- A proven track record of scientific contribution and independent research
- Prior experience with development of ML force fields and/or electronic structure methods
About Schrödinger
Schrödinger
schrodinger.com
13 other open roles at Schrödinger on TryApplyNow.
Frequently Asked Questions
How do I apply for the Machine Learning Force Field Scientist position at Schrödinger?
Use the Apply button above to submit your application directly to Schrödinger. Most applications take less than 5 minutes if your resume and contact details are ready, and you'll be routed to the employer's official application system to finish.
Where is the Machine Learning Force Field Scientist position at Schrödinger located?
This position is based in New York. Schrödinger has not indicated remote or hybrid options for this role, so candidates should plan for on-site work.
What does a Machine Learning Force Field Scientist at Schrödinger earn?
Schrödinger has not disclosed a salary range in this posting. Many employers share specifics later in the interview process; you can also ask during a recruiter screen if compensation transparency is important to you.
When was the Machine Learning Force Field Scientist role at Schrödinger posted?
This role was posted on July 1, 2026 (21 days ago). It's still listed as actively hiring; we re-confirm openings against the source system multiple times per day and remove closed roles.
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