Computational Scientist I/II, Soft Matter Formulations - Complex Fluids
Core
Develop machine learning models, tools, and workflows to accelerate discovery in liquid and flowable soft material systems, connecting composition, microstructure, and bulk fluid properties.
Role type
Senior IC computational scientist (soft matter & complex fluids)
Builds
Production ML models for complex fluid systems (colloids, emulsions, surfactants, polymers, coolants, coatings, inks, lubricants)
Domain
Materials science, soft matter physics, complex fluids, rheology, interfacial science
Deliverable
production ML models
Required skills
Machine learning for scientific/materials problems, Python, modern ML frameworks, domain expertise in colloids/emulsions/surfactants/polymer solutions/rheology/interfacial science, active learning over continuous compositional spaces, mesoscale/continuum simulation coupling (coarse-grained MD, dissipative particle dynamics, CFD), structure-property modeling
Preferred skills
Experimental data experience with complex fluids, modeling composition-to-microstructure-to-property relationships, high-throughput formulation campaigns, thermophysical fluid property modeling, hands-on experimental experience in soft material formulation
Technologies
Python, coarse-grained molecular dynamics, dissipative particle dynamics, CFD, active learning frameworks
Responsibilities
Develop ML models for complex fluid systems; Define modeling targets for rheology, phase stability, dispersion, aggregation, sedimentation, shelf-life, and thermophysical performance; Build structure-property models linking composition, microstructure, and bulk fluid behavior; Design active learning workflows to prioritize experiments; Incorporate mesoscale and continuum simulation outputs into ML workflows; Create tools for interpreting complex fluid data; Partner with experimental teams to align models with measurement workflows and development needs
Seniority
Senior, hands-on IC