Improve human health and quality of life through the development, distribution, and application of advanced computational methods by developing state-of-the-art ML force fields.
Requirements
Proficient Python programmer with prior knowledge of ML toolkits such as Scikit-Learn, NumPy, SciPy, Pandas, and PyTorch
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
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
Other
A PhD (or extensive experience) in Chemistry, Materials Science, Engineering, Computer Science, or Physics
A proven track record of scientific contribution and independent research
An innovator who’s driven to leverage technical knowledge to make a tangible impact
An independent researcher who enjoys collaborating with an interdisciplinary team in a fast-paced environment
A machine learning enthusiast with a background in physical science
