1

Computational Modeling Simulation Multiphysics Jobs in California

... multiphysics simulation engine-currently supporting high-pressure die casting and investment ... Leverage machine learning and AI solutions-such as surrogate modeling and physics-informed neural ...

... multiphysics simulation engine-currently supporting high-pressure die casting and investment ... Leverage machine learning and AI solutions-such as surrogate modeling and physics-informed neural ...

... multiphysics simulation engine-currently supporting high-pressure die casting and investment ... Leverage machine learning and AI solutions-such as surrogate modeling and physics-informed neural ...

This position is in the Computational Engineering Division (CED), within the Engineering ... modeling and simulation tools. * Advanced knowledge and experience, and demonstrated proficient ...

This position is in the Computational Engineering Division (CED), within the Engineering ... modeling and simulation tools. * Advanced knowledge and experience, and demonstrated proficient ...

This position is in the Computational Engineering Division (CED), within the Engineering ... modeling and simulation tools. * Advanced knowledge and experience, and demonstrated proficient ...

next page

Showing results 1-20

Computational Modeling Simulation Multiphysics information

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 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 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 some common challenges faced by professionals in Computational Modeling Simulation Multiphysics roles, 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 popular job titles related to Computational Modeling Simulation Multiphysics jobs in California? For Computational Modeling Simulation Multiphysics jobs in California, the most frequently searched job titles are:
What job categories do people searching Computational Modeling Simulation Multiphysics jobs in California look for? The top searched job categories for Computational Modeling Simulation Multiphysics jobs in California are:
What cities in California are hiring for Computational Modeling Simulation Multiphysics jobs? Cities in California with the most Computational Modeling Simulation Multiphysics job openings:
Infographic showing various Computational Modeling Simulation Multiphysics job openings in California as of May 2026, with employment types broken down into 49% Full Time, 39% Part Time, 6% Temporary, and 6% Contract. Highlights an 90% Physical, 5% Hybrid, and 5% Remote job distribution.

ML Engineer, Biological Analysis & Simulation

Mithrl

San Francisco, CA • On-site

$150K - $200K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 9 days ago


Job description

ABOUT MITHRL

We imagine a world where new medicines reach patients in months, not years, and where scientific breakthroughs happen at the speed of thought.

Mithrl is building the world’s first commercially available AI Co-Scientist. It is a discovery engine that transforms messy biological data into insights in minutes. Scientists ask questions in natural language, and Mithrl responds with real analysis, novel targets, hypotheses, and patent-ready reports.

Our traction speaks for itself:

  • 12X year-over-year revenue growth

  • Trusted by leading biotechs and big pharma across three continents

  • Driving real breakthroughs from target discovery to patient outcomes.

ABOUT THE ROLE

We are hiring an ML Engineer, Analysis and Simulation to build the core analytical and reasoning layer behind the Mithrl AI Co-Scientist. Your work will define how the AI interprets biological datasets, generates scientific conclusions, and orchestrates downstream simulation tools for drug discovery.

You will develop the reusable analysis modules that Mithrl runs for every dataset, and you will design multi step agentic workflows that combine statistical analysis, biological reasoning, and computational modeling. You will also integrate and experiment with simulation tools for small molecule discovery, such as ADMET prediction, docking scoring, Boltzmann generators and related computational chemistry engines.

This is the role that makes the AI Co-Scientist smart. If you have a strong background in ML, computational biology, and scientific analysis workflows, and you want to shape how AI reasons about biological systems, this is an exceptional opportunity.

WHAT YOU WILL DO

  • Build AI driven analysis agents that perform biological reasoning across a wide range of datasets

  • Develop the standard analysis suite for each dataset, including modules for differential expression, pathway analysis, feature importance, clustering, scoring, enrichment, and mechanism-of-action interpretation

  • Build multi step workflows that combine ML models, statistical logic, and biological knowledge to produce high confidence insights

  • Design and implement agentic reasoning strategies that allow Mithrl to run dozens analyses per dataset and synthesize the outputs into a coherent scientific narrative

  • Integrate simulation and modeling tools for small molecule drug discovery, including ADMET prediction, docking scoring, generative chemistry tools, structure based modeling, and related computational frameworks

  • Collaborate with the data engineering, bioinformatics, and curation teams to ensure analysis modules operate on clean and consistent data

  • Validate results, benchmark pipelines, and ensure scientific accuracy and reproducibility of all analyses

  • Contribute to the long term architecture for how the AI Co-Scientist performs reasoning, hypothesis testing, and simulation

WHAT YOU BRING

Required Qualifications

  • Strong experience in machine learning, computational biology, or a related scientific ML field

  • Experience developing analysis modules for biological or scientific datasets

  • Familiarity with common techniques in target discovery, gene expression analysis, pathway inference, clustering, or statistical modeling

  • Hands-on experience with computational chemistry or simulation tools, such as ADMET models, docking, binding prediction, or molecular generative models

  • Proficiency in Python and scientific computing libraries

  • Experience designing multi step reasoning or workflow based ML pipelines

  • Ability to translate messy scientific questions into structured ML or analytical workflows

  • Strong communication skills and comfort collaborating with cross functional scientific and engineering teams

Nice to Have

  • Experience with LLM powered scientific agents or multi agent architectures

  • Familiarity with phenotype based discovery, multi modal integration, or systems biology

  • Background in computational chemistry or structure based drug discovery

  • Experience with biological ontologies, curated knowledge graphs, or pathway databases

  • Prior experience in a tech bio company, biotech R&D group, or scientific platform team

WHAT YOU WILL LOVE AT MITHRL

  • High ownership: You will define how the AI Co-Scientist thinks and reasons about biology

  • Impact: You will work at the intersection of ML, biology, and simulation, with direct impact on real discovery programs

  • Team: Join a tight-knit, talent-dense team of engineers, scientists, and builders

  • Culture: We value consistency, clarity, and hard work. We solve hard problems through focused daily execution

  • Speed: We ship fast (2x/week) and improve continuously based on real user feedback

  • Location: Beautiful SF office with a high-energy, in-person culture

  • Benefits: Comprehensive PPO health coverage through Anthem (medical, dental, and vision) + 401(k) with top-tier plans

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

Compensation Range: $150K - $200K