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Computational Modeling Simulation Phd Jobs in California

Freeform

Senior Simulation Engineer

Los Angeles, CA · On-site

MS or PhD in applied mathematics, physics, computer science, mechanical engineering, or a related ... Experience with thermo-elastic or thermo-elastoplastic modeling * Familiarity with computational ...

Freeform

Senior Simulation Engineer

Los Angeles, CA · On-site

MS or PhD in applied mathematics, physics, computer science, mechanical engineering, or a related ... Experience with thermo-elastic or thermo-elastoplastic modeling * Familiarity with computational ...

Freeform

Senior Simulation Engineer

Los Angeles, CA

MS or PhD in applied mathematics, physics, computer science, mechanical engineering, or a related ... Experience with thermo-elastic or thermo-elastoplastic modeling * Familiarity with computational ...

Solidigm

3D NAND TCAD Modeling Engineer

San Jose, CA · On-site

$159K - $255K/yr

... or PhD in a related science or engineering discipline * 5~10 years of proven TCAD modeling ... Proficient with Synopsis process and device simulator tool suite * Experienced in computational ...

New

Voltai

Computational Scientist

Palo Alto, CA · On-site

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

Fuse

Computational Physicist

San Leandro, CA · On-site

Develop and run simulations for pulsed power systems using MHD, PIC, and circuit models. * Utilize ... Develop custom computational tools and optimize existing codes for high-performance computing (HPC)

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Computational Modeling Simulation Phd information

What is the difference between Computational Modeling Simulation Phd vs Computational Scientist?

AspectComputational Modeling Simulation PhdComputational Scientist
Required CredentialsPhD in computational sciences, engineering, or related fieldMaster's or PhD in computational or related fields
Work EnvironmentResearch labs, academia, industry R&DResearch institutions, tech companies, industry R&D
Industry UsageDeveloping models, simulations, and algorithms for complex systemsApplying computational methods to solve scientific or engineering problems

Both roles involve advanced computational skills and research experience, but the Computational Modeling Simulation Phd typically focuses on developing and validating models through extensive research, while a Computational Scientist applies these methods to practical problems across various industries.

What are popular job titles related to Computational Modeling Simulation Phd jobs in California? For Computational Modeling Simulation Phd jobs in California, the most frequently searched job titles are:
What job categories do people searching Computational Modeling Simulation Phd jobs in California look for? The top searched job categories for Computational Modeling Simulation Phd jobs in California are:
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Computational Modeling Simulation Phd jobs near you
Infographic showing various Computational Modeling Simulation Phd job openings in California as of June 2026, with employment types broken down into 89% Full Time, 10% Part Time, and 1% Temporary. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution.

Senior/Staff ML Engineer, 3D/4D World Modeling, Simulation

Waymo

Mountain View, CA • Hybrid

Full-time

Re-posted 27 days ago

Job description

The Simulator Team at Waymo builds state-of-the-art simulations of realistic environments for testing, training, and validation of the Waymo Driver. Our team is a diverse, and collaborative group of machine learning (ML) engineers, software engineers, and ML research engineers. We develop industry-leading simulation solutions using advanced generative and reconstructive ML algorithms, to model the real world, encompassing realistic agents, roads, traffic systems, weather, and the full sensor suite (Camera, Lidar, Radar).

To accelerate the fidelity, scalability, controllability, and richness of our simulations, we are pushing the frontiers of 3D world modeling. We leverage state-of-the-art ML technologies trained on large-scale datasets to create dynamic and semantically rich virtual worlds, directly impacting the development and validation of the Waymo Driver.

In this role, you will report to a Senior Staff Engineering Manager.

You will:

  • Lead the design, development and deployment of cutting-edge 4D world models and generative systems for ultra-realistic and controllable sensor and semantics generation for simulation use cases at waymo.
  • Architect and implement scalable and robust ML pipelines for training, evaluating, and deploying large-scale generative models into our simulation infrastructure, including techniques like model distillation and quantization.
  • Build and scale production-ready video generation techniques (e.g., Diffusion, Flow Matching) to create dynamic and interactive simulation environments.
  • Apply Vision Language Models (VLMs) to enhance the semantic understanding and controllability of our world simulation products.
  • Partner with world class research teams across Waymo and Alphabet to leverage State-of-The-Art research in 4D world modeling and generative AI into robust, production-ready solutions.
  • Mentor and provide technical guidance to other engineers on the team.

You have:

  • MS or PhD in Computer Science, Machine Learning, Robotics, or a related field.
  • 5+ years of experience in ML engineering and applied Deep Learning, with a strong portfolio of shipped products or publication record.
  • Proven experience in developing and training large-scale generative models for video generation (e.g., Diffusion models, Flow Matching) or Vision Language Models (VLMs) and their applications.
  • Deep expertise in 3D World Modeling or 3D computer vision.
  • Familiarity with 3D reconstruction and rendering techniques (e.g., 3D Gaussian Splatting).
  • Strong programming skills in Python and experience with ML frameworks such as Jax/Flax, PyTorch or Tensorflow.

We prefer:

  • PhD and a strong track record of delivering impactful ML products in 3D generative models, world models, or video generation..
  • Experience in simulating sensor data (Camera, Lidar, Radar) and/or semantic scenes.
  • Experience with autonomous systems, robotics, or autonomous vehicle simulation.
  • Experience in training and optimizing large scale models on GPU/TPU clusters for efficient serving.
  • Experience in C++ for production systems.

#LI-Hybrid

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