Machine Learning Force Fields Scientist
New York; Portland
Applications have closed
Schrödinger
Schrödinger is the scientific leader in developing state-of-the-art chemical simulation software for use in pharmaceutical, biotechnology, and materials research.Who will love this job:
- A machine learning enthusiast with a background in physical science
- 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 Scikit-Learn, NumPy, SciPy, Pandas, and PyTorch
- 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
Tags: Chemistry Computer Science Engineering Machine Learning NumPy Pandas PhD Physics Python PyTorch Research Scikit-learn SciPy
Perks/benefits: 401(k) matching Career development Competitive pay Equity Flex hours Flex vacation Health care Lunch / meals Parental leave Team events
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