Research Scientist, Soft Matter Simulations

Crosslinked

Jobs/Thermoplastics/Research Scientist, Soft Matter Simulations

One of 8,200 open polymer and materials roles on Crosslinked, each read for materials, degree, visa and salary. See roles like this

H-1B history This employer has filed H-1B petitions with the U.S. Department of Labor in the past. That is a record of prior filings, not a statement about this role. Whether any given position is eligible for sponsorship is decided by the employer, case by case. Confirm before you apply. From Jan to Dec 2025 it filed 4 H-1B labor applications for scientist and engineer roles.

Research Scientist, Soft Matter Simulations

Lila Sciences

• Cambridge, MA - today - verified 9 h ago
• $176k – $304k from the posting

PhD-level R&D / Research roles on Crosslinked list a median of $134k (156 that show pay).

Apply soft matter simulation (MD, DPD, SCFT) and agentic AI to discover and optimize polymer and formulated fluid systems.

Computational or desk

Deep specialist PhD-friendly

Core polymer role: applying soft matter physics and molecular simulation to polymers, colloids, surfactants, gels, liquid crystals; MD, DPD, SCFT, structure-property relationships

H-1B filings

Lila Sciences filed 4 H-1B labor applications for scientist and engineer roles from Jan to Dec 2025.

Most common titles:
Senior Engineer II, Controls, Senior Engineer II, Automation, Research Associate II. Median filed pay: $145K a year.

From U.S. Department of Labor disclosure data. A filing is a record of past hiring, not a promise about this role, so confirm sponsorship with the employer. Titles and filed pay

Seniority Mid-level

Work On-site

Type Full-time

Degree PhD

Industry Chemicals

Role R&D / Research

Materials

polymers,566 rolescolloids,12 rolessurfactants,31 rolesgels,6 rolesliquid crystals,3 roles

molecular dynamics,19 rolesdissipative particle dynamics

Monte Carlo,3 rolesself-consistent field theory,2 rolesliquid state theory

Your role will involve applying soft matter physics and molecular simulation expertise to accelerate the discovery, optimization, and understanding of complex soft matter systems. You will use coarse-grained and atomistic modeling, mesoscale simulation, analytical theory, and agentic AI systems to investigate polymers, colloids, surfactants, gels, liquid crystals, and formulated fluid systems with direct relevance to commercial applications.

You will work at the intersection of physics-based simulation, AI/ML, and autonomous scientific workflows. The focus is on using computational insight to identify promising formulations and material compositions, explain structure-property relationships, guide optimization campaigns, and help agents reason over simulation and experimental data in scientifically grounded ways. Desired simulation expertise covers atomistic and coarse-grained molecular dynamics, mesoscale approaches such as dissipative particle dynamics, Monte Carlo sampling, and analytical theory including self-consistent field theory, field theoretic simulation, and liquid state theory.

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.

• 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

• PhD in chemical…