About the job
Make an Impact at Lila Sciences
As a pivotal member of our Physical Sciences division, you will spearhead the design and implementation of cutting-edge simulation methodologies aimed at modeling transport phenomena, kinetics, rare events, and reaction networks. Your innovative approaches will be integrated with artificial intelligence platforms to facilitate groundbreaking materials discovery. Your contributions will be essential in predicting, designing, and managing the behaviors of intricate materials and molecular systems, leveraging the power of agentic AI. Collaborating with our diverse teams, including experts in machine learning and materials science, you will help bridge theoretical research and practical experimentation.
What You Will Create
- Enhance and develop molecular dynamics and Monte Carlo algorithms to effectively capture rare events, non-equilibrium processes, transport phenomena, and intricate reaction networks.
- Create scalable simulation workflows that merge statistical mechanics techniques with machine-learned interatomic potentials and agentic AI systems.
- Devise methods for synchronizing dynamic simulations with experimental observations to enable automated lab verification and discovery.
- Work collaboratively with computational scientists, machine learning specialists, and platform engineers to elevate the accuracy and scalability of simulation-driven material discoveries.
- Establish reproducible and modular software pipelines for statistical mechanics and dynamics simulations, optimized for high-performance computing and cloud environments.
Qualifications for Success
- A PhD or equivalent research/industry experience in Physics, Chemistry, Chemical Engineering, Mechanical Engineering, Applied Mathematics, or related fields.
- A robust background in statistical mechanics, free energy calculations, reaction mapping, non-equilibrium dynamics, and rare-event sampling techniques.
- Proven expertise in molecular dynamics, Monte Carlo simulations, and/or kinetic simulation software frameworks (e.g., LAMMPS, GROMACS, OpenMM, HOOMD).
- Strong programming skills and experience in scientific computing (Python, C/C++, MPI, CUDA, etc.).
- Experience in executing and automating simulations on high-performance computing (HPC) and/or cloud platforms at scale.
Bonus Qualifications
- A solid publication record showcasing the application of advanced statistical mechanics or dynamics simulations to molecular and materials systems, including molecular/biomolecular systems and solid-state materials and interfaces.
- Experience in integrating dynamics simulations with data-driven, AI-based, and/or agentic frameworks.

