Computational Scientist I/II, Soft Matter Formulations - Complex Fluids

Your Impact at LILA Lila Sciences is seeking a Computational Scientist I/II, Soft Matter Formulations - Complex Fluids to develop models, tools, and workflows that accelerate discovery across liquid and flowable soft material systems. This role focuses on complex fluids, including colloidal suspensions, emulsions, surfactant systems, polymer solutions, coolants and heat-transfer fluids, coatings, inks, and lubricants. You will bring domain expertise in soft matter, complex fluids, colloids, rheology, interfacial science, formulation science, or a closely related area, and apply machine learning methods to connect composition, microstructure, processing conditions, and bulk fluid properties. The work spans rheology and flow behavior, phase stability, dispersion and aggregation, sedimentation, shelf-life, interfacial and wetting behavior, surface tension, foaming, and thermophysical performance. This is a hands-on scientific ML role for someone who can bridge domain context and computational execution. You will develop structure-property models linking composition to microstructure and bulk fluid behavior, build active learning workflows over continuous compositional spaces, and incorporate mesoscale or continuum simulation coupling, such as coarse-grained molecular dynamics, dissipative particle dynamics, or CFD hooks, where it improves prediction and experimental decision-making. What You'll Be Building

Develop machine learning models for complex fluid systems, including colloidal suspensions, emulsions, surfactant systems, polymer solutions, coolants and heat-transfer fluids, coatings, inks, and lubricants. Define modeling targets for rheology, phase stability, dispersion and aggregation behavior, sedimentation, shelf-life, and thermophysical performance for liquid formulation systems, Build structure-property models that connect composition, microstructure, processing conditions, and bulk fluid properties. Design active learning workflows over continuous compositional spaces that prioritize high-value experiments and formulation decisions. Incorporate mesoscale and continuum simulation outputs, such as coarse-grained MD, dissipative particle dynamics, or CFD-linked features, where they improve prediction or interpretation. Create tools that help scientists interpret complex fluid data and prioritize formulation, processing, or composition decisions. Partner with experimental teams to align models with measurement workflows, formulation workcell throughput, material performance requirements, and practical development needs. Communicate model behavior, uncertainty, and recommendations to scientific, engineering, and cross-functional collaborators.

What You'll Need to Succeed

Experience applying machine learning to scientific, materials-focused, complex fluid, soft matter, or formulation problems. Domain expertise in colloids, emulsions, surfactants, polymer solutions, rheology, interfacial science, thermophysical fluids, coatings, inks, lubricants, or related fields. Familiarity with rheology, phase stability, dispersion, aggregation, sedimentation, wetting, surface tension, foaming, thermal conductivity, heat capacity, or related fluid performance properties. Strong Python skills and experience with modern ML frameworks. Experience training, evaluating, and improving models using experimental, simulation, or scientific datasets. Ability to use simulations, theory, descriptors, or mechanistic understanding to inform modeling choices for complex fluid systems. Strong communication skills with experimental, computational, and cross-functional collaborators. PhD in chemical engineering, materials science, physics, applied mathematics, computational science, or a related field, or a master’s degree with equivalent relevant experience.

Bonus Points For

Experience working with experimental data from colloidal suspensions, emulsions, surfactant systems, polymer solutions, coolants, coatings, inks, lubricants, or related liquid formulations. Experience modeling composition-to-microstructure-to-property relationships for liquid or flowable soft material systems. Familiarity with active learning over continuous compositional spaces or high-throughput formulation campaigns. Experience incorporating mesoscale or continuum simulation outputs, including coarse-grained MD, dissipative particle dynamics, CFD-linked models, or related approaches, into ML workflows. Experience modeling thermophysical fluid properties relevant to coolant or heat-transfer applications. Hands-on experimental experience in complex fluids, colloids, emulsions, rheology, interfacial science, or soft material formulation domains. Compensation We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact. U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program. International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market. Expected Base Salary Range $118,800 — $187,000 USD About LILA Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves. LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai. Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply. We’re All In Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy . A Note to Agencies Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.