Research Scientist, Soft Matter Simulations

Alewife, Cambridge, MAfull timeOn Site

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$176k–$304k

H1B: no

Lila Sciences Research Scientist applying soft matter physics and molecular simulation expertise to accelerate discovery and optimization of complex soft matter systems. Develops simulation capabilities and agentic AI systems for autonomous scientific workflows.

Responsibilities

This is a hands-on research role for someone who can connect deep soft matter and molecular simulation expertise with software development and practical scientific impact. You will collaborate with computational scientists, AI researchers, software engineers, and experimental teams to turn simulations, models, and scientific reasoning into robust software, agentic frameworks, and closed-loop scientific workflows.
What You'll Be Building
Implement, extend, and deploy atomistic, coarse-grained, and mesoscale simulation capabilities for soft matter systems, including MD, DPD, SCFT, Monte Carlo, and liquid state theory
Engineer simulation software with modern scientific libraries, emphasizing testing, modularity, and reproducibility at scale on HPC and cloud infrastructure
Translate simulation outputs into descriptors and datasets for ML models, and build predictive models to guide formulation selection and optimization
Develop and deploy agentic AI systems that leverage simulation capabilities for autonomous scientific discovery and closed-loop experimentation
Communicate physical insights, model limitations, and recommendations to computational, ML, and experimental collaborators

Qualification

PhD in chemical engineeringWorking knowledge of at least two of

Required

PhD in chemical engineering, physics, materials science, chemistry, or a related field (or master's with equivalent experience)
Strong background in soft matter physics covering polymers, colloids, surfactants, gels, or liquid crystals, with hands-on expertise in atomistic and coarse-grained MD
Working knowledge of at least two of: DPD or other mesoscale methods, Monte Carlo, SCFT, field theoretic simulation, or liquid state theory
Strong Python scientific software development skills; fluency with modern practices including version control, testing, code review, and packaging
Experience running and automating simulations at scale on HPC or cloud, and integrating computational predictions into experimental or closed-loop optimization workflows
Good familiarity with agentic AI systems, autonomous scientific workflows, or simulation-aware agents

Preferred

Experience with a compiled language (C++, Rust, or Fortran) for performance-critical simulation code, or GPU acceleration via JAX or PyTorch
Contributions to open source simulation packages such as LAMMPS, HOOMD-blue, GROMACS, or OpenMM
Experience developing ML potentials or applying AI/ML to soft matter simulation data and molecular property prediction
Experience building agents that reason over or orchestrate simulation workflows, or coupling simulation to active learning and Bayesian optimization pipelines
Publication record in soft matter theory and simulation

Benefits

Dental
Vision
Equity/RSU
Parental Leave
Life Insurance

Company

Lila Sciences

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Source: greenhouse

Active within the past hour

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