Machine Learning Force Field Scientist

Role: ML Scientist focused on developing and validating ML force fields for life and materials sciences applications, leveraging Schrödinger’s physics-based software platform. Responsibilities: build large quantum chemical datasets, develop software to train/apply ML force fields, extend their accuracy and versatility, and present findings to multidisciplinary teams. Requirements: PhD or extensive experience in Chemistry, Materials Science, Engineering, Computer Science, or Physics; proven research track record; experience with ML force fields and electronic structure methods; proficient in Python and ML tools like PyTorch, Scikit-Learn, NumPy, SciPy, Pandas. High-Value: focus on complex condensed-phase systems, such as solvated biomolecules and interfaces; development of ML force fields for impactful applications in biology and materials; collaborative, fast-paced R&D environment. WorkSetup: not specified; likely hybrid or remote depending on location.