ML Force Field Scientist — Flexible Schedule

Schrödinger; New York (NY); On-site; USD 120,000 - 175,000; Full time

Benefits offered by this job

Healthcare

401k

Commuter benefits

Flexible schedule

Parental leave

Paid vacation

Job summary

Schrödinger is seeking a Machine Learning (ML) Scientist to advance the discovery of therapeutics and materials using physics-based software for efficient molecule design. The role focuses on building ML force fields, training models, and applying them to complex condensed-phase systems in collaboration with an interdisciplinary team.

The ideal candidate has a PhD (or extensive experience) in a relevant field, strong experience with ML toolkits (PyTorch, Scikit-Learn, NumPy, SciPy, Pandas), and

Qualifications

• 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.

Responsibilities

• 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.

Skills

Python

ML toolkits

PyTorch

Scikit-Learn

NumPy

SciPy

Pandas

DFT

Electronic structure

Independent research

Education

PhD in Chemistry / Materials Science / Engineering / CS / Physics

Tools

Quantum chemistry software

Job description

Schrödinger is seeking a Machine Learning (ML) Scientist to advance the discovery of therapeutics and materials using physics-based software for efficient molecule design. The role focuses on building ML force fields, training models, and applying them to complex condensed-phase systems in collaboration with an interdisciplinary team.

The ideal candidate has a PhD (or extensive experience) in a relevant field, strong experience with ML toolkits (PyTorch, Scikit-Learn, NumPy, SciPy, Pandas), and