Research Scientist, Soft Matter Simulations

Lila Sciences
Cambridge +3 more
On-site

Who this role is best for

Geared toward candidates with deep soft matter physics expertise and software development experience, comfortable with deploying simulations and AI systems across HPC and cloud infrastructure in a collaborative, interdisciplinary setting.

Best fit for

  • Candidates with a PhD in physics or materials science and experience in both simulation and AI/ML development
    — “PhD in chemical engineering, physics, materials science, chemistry, or a related field (or master's with equivalent experience)”
  • Individuals who have developed and deployed simulation software with emphasis on modularity and testing
    — “Engineer simulation software with modern scientific libraries, emphasizing testing, modularity, and reproducibility at scale on HPC and cloud infrastructure”
  • Those with a track record of integrating simulation results into experimental or optimization workflows
    — “Experience running and automating simulations at scale on HPC or cloud, and integrating computational predictions into experimental or closed-loop optimization workflows”

Things to consider

  • The role demands a strong balance between theoretical physics and practical software development skills
    — “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”
  • Candidates must be prepared to work in a fast-moving startup environment with high autonomy
    — “Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance”

How to stand out

  • Highlight experience with agentic AI systems and autonomous discovery workflows in your resume
    — “Develop and deploy agentic AI systems that leverage simulation capabilities for autonomous scientific discovery and closed-loop experimentation”
  • Emphasize contributions to open source simulation software or ML potentials for soft matter systems
    — “Contributions to open source simulation packages such as LAMMPS, HOOMD-blue, GROMACS, or OpenMM”
  • Demonstrate your ability to translate simulation outputs into ML-ready datasets
    — “Translate simulation outputs into descriptors and datasets for ML models, and build predictive models to guide formulation selection and optimization”
  • Showcase your experience with both atomistic and coarse-grained molecular dynamics methods
    — “Desired simulation expertise covers atomistic and coarse-grained molecular dynamics, mesoscale approaches such as dissipative particle dynamics, Monte Carlo sampling, and analytical theory”
  • Demonstrate fluency in Python scientific software development and version control practices
    — “Strong Python scientific software development skills; fluency with modern practices including version control, testing, code review, and packaging”
Pace · Fast PacedCollaboration · HighAutonomy · HighDecision Impact · Company

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • acceleration of discovery and optimization of complex soft matter systems
  • development of agentic AI systems
Typical background
chemical engineeringphysicsmaterials science

Skills & requirements

Required

Soft Matter PhysicsMolecular SimulationAi/mlScientific Software DevelopmentSimulation Software EngineeringAgentic AI Systems

Preferred

Compiled Language For Simulation CodeGPU AccelerationOpen Source Simulation Packages

Stack & domain

Soft Matter PhysicsMolecular SimulationCoarse-grained ModelingMesoscale SimulationAnalytical TheoryAgentic AI SystemsAtomistic And Coarse-grained MDDPDMonte CarloSCFTField Theoretic SimulationLiquid State TheoryPython Scientific Software DevelopmentVersion ControlTestingCode ReviewPackagingHPCCloud InfrastructureML ModelsClosed-loop Scientific WorkflowsC++RustFortranGPU AccelerationJAXPyTorchLammpsHoomd-blueGromacsOpenmmProblem-solvingCommunicationCollaborationTeamworkSoft Matter SystemsPolymersColloidsSurfactantsGelsLiquid CrystalsFormulated Fluid SystemsCommercial ApplicationsPhysics-based SimulationAi/mlAutonomous Scientific WorkflowsComputational InsightFormulation SelectionOptimizationSimulation-aware Agents

About the role

Original posting from Lila Sciences via Greenhouse

Your Impact at LILA

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.

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

What You'll Need to Succeed

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

Bonus Points For

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

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$176,000—$304,000 USDAbout 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.

Source: Lila Sciences careers (Greenhouse)

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