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Computational Modeling Simulation Multiphysics Jobs in Boston, MA

Lead advanced FEA and multiphysics simulations to support design, optimization, and troubleshooting of complex systems. * Own analysis activities end-to-end, including model setup, validation, and ...

Develop and execute test methods and simulation models to mitigate design risks and ensure product ... Exposure to computational modeling, fluid dynamics, and hemocompatibility testing. * Experience ...

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Computational Modeling Simulation Multiphysics information

See Boston, MA salary details

$42.4K

$110K

$156.4K

How much do computational modeling simulation multiphysics jobs pay per year?

As of Aug 21, 2026, the average yearly pay for computational modeling simulation multiphysics in Boston, MA is $110,004.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,300.00 and $140,700.00 per year, depending on experience, location, and employer.

What is computational modeling simulation multiphysics?

Computational modeling simulation multiphysics refers to the use of computer-based models to simulate and analyze systems that involve multiple interacting physical phenomena—such as fluid dynamics, heat transfer, electromagnetics, and structural mechanics—all at once. This approach allows researchers and engineers to predict complex real-world behavior, optimize designs, and reduce the need for expensive prototypes. Multiphysics simulations are widely used in industries like aerospace, automotive, energy, and biomedical engineering, where accurate modeling of coupled physical processes is critical.

What are common challenges faced by professionals in computational modeling simulation multiphysics, and how can they be addressed?

One of the main challenges in Computational Modeling Simulation Multiphysics roles is managing the complexity of integrating multiple physical phenomena, such as thermal, structural, and fluid dynamics, into a single simulation. This often requires a deep understanding of both the underlying physics and the numerical methods used by simulation software. Collaborating closely with domain experts and maintaining clear communication within multidisciplinary teams can help address these challenges. Additionally, staying updated with advances in simulation tools and best practices through continuous learning is key to overcoming technical hurdles and ensuring accurate results.

What are the key skills and qualifications needed to thrive as a computational modeling simulation multiphysics engineer, and why are they important?

A strong background in physics, engineering, mathematics, and computational science—typically with an advanced degree—is essential for a Computational Modeling Simulation Multiphysics Engineer. Proficiency in simulation software such as ANSYS, COMSOL Multiphysics, MATLAB, and programming languages like Python or C++ is commonly required, along with familiarity with high-performance computing environments. Analytical thinking, problem-solving skills, and effective communication set standout professionals apart in this field. These capabilities enable accurate modeling of complex physical phenomena, efficient collaboration, and successful project outcomes in research and industry settings.

What is the difference between Computational Modeling Simulation Multiphysics vs Computational Engineer?

AspectComputational Modeling Simulation MultiphysicsComputational Engineer
CredentialsTypically requires degrees in engineering, physics, or related fields; certifications in simulation software are commonSimilar educational background; often holds engineering degrees and software certifications
Work EnvironmentPrimarily in R&D labs, engineering firms, or manufacturing settings focusing on complex simulationsInvolved in product development, software development, or systems design in various industries
Industry UsageUsed in aerospace, automotive, energy, and manufacturing for advanced simulationsApplied across industries for designing, analyzing, and optimizing systems and products

While both roles involve computational skills and engineering principles, Computational Modeling Simulation Multiphysics specializes in complex, multi-physics simulations, whereas Computational Engineer focuses on designing and implementing computational solutions across various engineering projects.

What are popular job titles related to Computational Modeling Simulation Multiphysics jobs in Boston, MA?

For Computational Modeling Simulation Multiphysics jobs in Boston, MA, the most frequently searched job titles are:

What job categories do people searching Computational Modeling Simulation Multiphysics jobs in Boston, MA look for?

The top searched job categories for Computational Modeling Simulation Multiphysics jobs in Boston, MA are:

What cities near Boston, MA are hiring for Computational Modeling Simulation Multiphysics jobs?

Cities near Boston, MA with the most Computational Modeling Simulation Multiphysics job openings:

Scientist II/Senior Scientist, Computational Biophysics

Lila Sciences

Cambridge, MA • On-site

Full-time

Medical, Dental, Vision, Life

Posted 18 days ago


Job description

Your Impact at LILA
Lila Sciences is seeking a Computational Biophysics Scientist to help ensure that our AI agents can use biophysics tools in ways that are scientifically correct, reliable, and useful for drug discovery. This person will define how biophysics experiments should be set up, parameterized, validated, and exposed as tools for automated scientific workflows.
The role sits at the intersection of computational biophysics, molecular simulation, and agentic platform design. You will work with computational scientists, research engineers, ML scientists, and drug discovery teams to build a scalable biophysics platform capable of running across hundreds of GPUs while preserving scientific rigor. This is a hands-on scientific role: the expectation is not heavy production software engineering, but strong ownership of the scientific logic, validation standards, and tool requirements that make automated biophysics trustworthy.
This role is differentiated from the broader computational chemistry position by its depth in statistical mechanics, molecular simulation, and the theory, setup, and validation of relative and absolute binding free-energy methods.
This role is one part of a broader agentic drug discovery system: computational chemistry helps judge whether agent-generated optimization strategies are chemically sensible, ML scientists build cofolding and low-data learning models, and research engineers help turn validated scientific protocols into reliable scalable infrastructure.
What You'll Be Building
  • Define the scientific requirements for agent-usable computational biophysics tools, including what inputs are required, what assumptions are acceptable, and what outputs are decision-grade.
  • Design and validate molecular simulation workflows for drug discovery applications, including MM/GBSA and free-energy perturbation methods for relative and absolute binding free energies (RBFE/ABFE).
  • Establish standards for system setup, force field selection, molecular parameterization, equilibration, sampling, analysis, and quality control.
  • Build robust, validated RBFE and ABFE workflows with automated checks for chemical-series compatibility, ligand-pose consistency, and other conditions required for trustworthy agent use.
  • Work with research engineers to turn biophysics protocols into reliable tools, APIs, and guardrails that LLM agents can invoke correctly.
  • Build validation benchmarks and acceptance criteria for molecular dynamics, binding free-energy, and related computational workflows.
  • Evaluate and integrate open-source molecular simulation and free-energy tools, especially OpenMM, OpenFE, and adjacent packages.
  • Identify and mitigate failure modes in simulation setup, parameterization, sampling, analysis, and interpretation.
  • Advise teams on when a biophysics workflow is appropriate, what evidence it can support, and where its limitations matter.
  • Partner with ML teams to refine molecular simulation methods and parameters as new experimental data becomes available.
  • Partner with research engineering and infrastructure teams to scale validated workflows across large GPU fleets with reproducibility and traceability.

What You'll Need to Succeed
  • PhD or equivalent experience in computational biophysics, computational chemistry, chemical physics, biophysics, physics, chemistry, or a related field.
  • Deep hands-on experience with molecular dynamics simulation, MM/GBSA, and free-energy perturbation methods for RBFE and ABFE.
  • Practical experience with open-source molecular simulation and free-energy packages, with strong preference for OpenMM and OpenFE.
  • Strong understanding of how to parameterize molecular systems and validate that simulation setups are scientifically sound.
  • Demonstrated history of modeling protein-ligand binding and interpreting results for scientific decision-making.
  • Ability to reason from biophysical first principles while also building practical workflows that other teams can use.
  • Experience translating complex scientific methods into tooling requirements, review standards, and operational workflows.
  • Strong cross-functional communication skills and comfort working with computational scientists, ML researchers, research engineers, and drug discovery teams.

Bonus Points For
  • Industry drug discovery experience, especially in structure-based or computational discovery programs.
  • Familiarity with large-scale GPU simulation infrastructure or distributed scientific computing.
  • Experience building automated or semi-automated scientific workflows.
  • Familiarity with cofolding, structure prediction, or ML-assisted molecular modeling methods.
  • Experience defining benchmark suites, regression tests, or validation harnesses for scientific software.
  • Experience designing perturbation maps for robust RBFE statistics.
  • Experience integrating machine-learned interatomic potentials or hybrid force-field simulations.
  • Experience with active learning or fine-tuning of simulation parameters against experimental data for defined chemical or biological systems.
  • Comfort working with LLM agents or agentic workflow systems.

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
$140,800-$217,800 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.