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Computational Modeling Simulation Multiphysics Jobs in Santa Clara, CA

Apple

Biomedical Modeling Scientist

Cupertino, CA

$129K - $225K/yr

... simulation infrastructure.","responsibilities":"You will be responsible for building and validating computational models of light transport in skin to support research objectives. This will involve ...

Voltai, Inc

Computational Scientist

Palo Alto, CA · On-site

Design simulation pipelines that generate training data for neural operator models - including ... PhD in computational physics, applied mathematics, computational engineering, or a closely related ...

Voltai

Computational Scientist

Palo Alto, CA · On-site

Design simulation pipelines that generate training data for neural operator models -- including ... PhD in computational physics, applied mathematics, computational engineering, or a closely related ...

Mainspring Energy

Staff CFD Modeling Engineer

Menlo Park, CA · On-site +1

$160K - $190K/yr

Extract fluid volumes suitable for computational analysis. Generate, refine, and debug the mesh to achieve a stable and accurate simulation * Select appropriate boundary conditions and domain models ...

Mainspring Energy

Staff CFD Modeling Engineer

Menlo Park, CA · On-site +1

$160K - $190K/yr

Extract fluid volumes suitable for computational analysis. Generate, refine, and debug the mesh to achieve a stable and accurate simulation * Select appropriate boundary conditions and domain models ...

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All JobsComputational Modeling Simulation Multiphysics JobsComputational Modeling Simulation Multiphysics Jobs in Santa Clara, CA

Computational Modeling Simulation Multiphysics information

See Santa Clara, CA salary details

$45.8K

$118.9K

$169.1K

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

As of Sep 12, 2026, the average yearly pay for computational modeling simulation multiphysics in Santa Clara, CA is $118,918.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,200.00 and $152,100.00 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 Santa Clara, CA?

For Computational Modeling Simulation Multiphysics jobs in Santa Clara, CA, the most frequently searched job titles are:

What job categories do people searching Computational Modeling Simulation Multiphysics jobs in Santa Clara, CA look for?

The top searched job categories for Computational Modeling Simulation Multiphysics jobs in Santa Clara, CA are:

What cities near Santa Clara, CA are hiring for Computational Modeling Simulation Multiphysics jobs?

Cities near Santa Clara, CA with the most Computational Modeling Simulation Multiphysics job openings:

Computational Modeling Simulation Multiphysics jobs near you
Infographic showing various Computational Modeling Simulation Multiphysics job openings in Santa Clara, CA as of June 2026, with employment types broken down into 100% Part Time. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $118,918 per year, or $57.2 per hour.

Senior Machine Learning Scientist I, Drug Discovery Analytics

Redwood City, CA • Hybrid

Revolution Medicines
See more jobs at Revolution Medicinesexternal

$112K - $153K/yr

Full-time

Re-posted 18 days ago

Job description

The Opportunity:

We are seeking a Senior Machine Learning Scientist to help accelerate drug discovery through advanced analytics and artificial intelligence. This role will develop predictive models and analytical methods that transform complex biological and chemical datasets into actionable insights that guide research decisions.

The Senior Machine Learning Scientist will work at the interface of data science, chemistry, and biology to support target discovery, compound optimization, and translational research. This position requires both strong machine learning expertise and the ability to collaborate effectively with experimental scientists to solve real-world scientific problems.

The successful candidate will contribute to building a data-driven discovery ecosystem where data, analytics, and experimentation continuously inform and accelerate one another.
Key responsibilities include:

  • Develop Predictive Models for Drug Discovery.

  • Independently Design and implement machine learning models to predict compound activity, selectivity, and developability.

  • Identify and Develop predictive frameworks for ADME/Tox, target engagement, and phenotypic screening outcomes.

  • Apply advanced modeling approaches including deep learning, graph neural networks, and ensemble methods.

  • Evaluate model performance and apply appropriate validation strategies.

  • Work with data engineers and ML engineers to integrate models into discovery pipelines.

  • Analyze Complex Scientific Data.

  • Perform exploratory data analysis on chemical, biological, and phenotypic datasets.

  • Integrate heterogeneous datasets including:

  • Chemical structure and screening data.

  • Structural biology and molecular simulation outputs.

  • Collaborate with Research Scientists.

  • Partner with medicinal chemists to support compound design and lead optimization.

  • Work with biologists to interpret experimental results and identify new target opportunities.

  • Translate scientific questions into computational modeling strategies.

Required Skills, Experience and Education:

  • PhD in machine learning, computational biology, computational chemistry, computer science, statistics, or a related quantitative field.

  • 6-10 years of experience applying machine learning or advanced analytics to scientific datasets.

  • Python and scientific computing libraries (NumPy, Pandas, SciPy).

  • Machine learning frameworks (PyTorch, TensorFlow, scikit-learn).

  • Model development, validation, and evaluation methods.

  • Data visualization and exploratory analysis.

  • Experience working with noisy and incomplete experimental datasets.

Preferred Skills:

  • Cheminformatics or molecular modeling tools (RDKit, OpenEye, etc.).

  • Multi-omics data analysis.

  • Cloud computing environments.

  • MLOps or scalable model deployment. 

    #LI-Hybrid  #LI-LN1

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