Business Services & Consulting • all cities, MS 26
Chemical Physics (Enhanced Sampling, MLIPs) (26)
all cities, MS 26On-sitePosted 1 day ago
Business Services & Consulting
About the Role
Chemical Physics (Enhanced Sampling, MLIPs)
Bay Area preferred; exceptional remote candidates considered Full-Time
Startup salary + substantial equity
Job Description
We're looking for someone with strong expertise in molecular dynamics, enhanced sampling methods (e.g., metadynamics, umbrella sampling, replica exchange), free energy calculations, computational thermodynamics, deep learning, and force-field / neural network potential development. Experience with electronic structure methods (DFT) and statistical mechanics is a major plus.
What You'll Do
Lead or contribute to MD, enhanced sampling, and free energy projects
Develop and deploy high-accuracy force fields and neural network potentials
Build deep learning models for molecular and materials prediction (PyTorch or similar)
Write efficient scientific software in Python and/or C++
Take ideas from theory to scalable implementation
Who You Are
PhD in chemical physics, chemistry, physics, materials science, or related field
Strong background in MD, enhanced sampling, free energy methods, force-field/NN-potential development, and deep learning for molecular systems
Experience with electronic structure (DFT), statistical mechanics, or rare-event methods
Proficient in scientific programming; parallel tools a plus
Preferred: OpenMM, OpenFE, and training MLIPs (e.g., MACE, etc.)
Why Azulene Labs
High-impact science with real-world consequences
Significant equity as an early technical leader
Deep-thinking, high-expectation environment
Chemical Physics (Enhanced Sampling, MLIPs)
Bay Area preferred; exceptional remote candidates considered Full-Time
Startup salary + substantial equity
Job Description
We're looking for someone with strong expertise in molecular dynamics, enhanced sampling methods (e.g., metadynamics, umbrella sampling, replica exchange), free energy calculations, computational thermodynamics, deep learning, and force-field / neural network potential development. Experience with electronic structure methods (DFT) and statistical mechanics is a major plus.
What You'll Do
Lead or contribute to MD, enhanced sampling, and free energy projects
Develop and deploy high-accuracy force fields and neural network potentials
Build deep learning models for molecular and materials prediction (PyTorch or similar)
Write efficient scientific software in Python and/or C++
Take ideas from theory to scalable implementation
Who You Are
PhD in chemical physics, chemistry, physics, materials science, or related field
Strong background in MD, enhanced sampling, free energy methods, force-field/NN-potential development, and deep learning for molecular systems
Experience with electronic structure (DFT), statistical mechanics, or rare-event methods
Proficient in scientific programming; parallel tools a plus
Preferred: OpenMM, OpenFE, and training MLIPs (e.g., MACE, etc.)
Why Azulene Labs
High-impact science with real-world consequences
Significant equity as an early technical leader
Deep-thinking, high-expectation environment
What You'll Do
Lead or contribute to MD, enhanced sampling, and free energy projects
Develop and deploy high-accuracy force fields and neural network potentials
Build deep learning models for molecular and materials prediction (PyTorch or similar)
Write efficient scientific software in Python and/or C++
Take ideas from theory to scalable implementation
PhD in chemical physics, chemistry, physics, materials science, or related field
